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      "cell_type": "markdown",
      "source": [
        "# ESG Discourse and AI Semantic Analysis in Urban Digital Twin Enterprises: A Comparative Study of China and the United States\n",
        "\n",
        "\n",
        "*   **Author:** Jocelyn Yuan\n",
        "*   **Affiliation:** Richard Montgomery High School\n",
        "\n",
        "This lab explores how large language models (LLMs), specifically Google Gemini, can be prompted to perform semantic analysis on corporate sustainability reports. Focusing on two urban digital twin enterprises from China and the United States, respectively, you will design and apply a prompt that guides the LLM to assess report content across specific ESG (environmental, social and governance) criteria and regulatory/cultural contexts.\n",
        "\n",
        "Through a comparison with a traditional quantitative approach, you will evaluate Gemini's ability to not only compare the reports' content, but also insights into the discourse, emphasis, and narrative framing within the sustainability reports. This lab combines natural language processing, prompt engineering, cultural analysis, and critical reasoning to examine the strengths and weaknesses of LLMs in AI semantic analysis.\n",
        "\n",
        "### Objectives:\n",
        "\n",
        "By completing this lab, you will:\n",
        "\n",
        "- Configure and use Google Gemini within a Colab environment to analyze PDF-based ESG reports.\n",
        "- Write structured prompts that ask an LLM to score corporate disclosures across nine ESG subcategories.\n",
        "- Interpret and evaluate Gemini’s ESG scoring output, including its justifications and formatting.\n",
        "- Conduct follow-up semantic analysis by prompting the model to clarify or reflect on its own decisions.\n",
        "- Compare LLM-based ESG evaluation with traditional metrics, such as keyword frequency or sentiment analysis.\n",
        "- Identify cultural and narrative differences in sustainability discourse between Chinese and U.S. companies.\n",
        "- Reflect on the challenges, limitations, and ethical implications of using generative AI for corporate accountability and cross-cultural ESG benchmarking.\n",
        "\n",
        "### Lab Workflow\n",
        "\n",
        "- **Environment Setup**: Install required libraries and configure Gemini API access.\n",
        "- **Document Preparation**: Load corporate sustainability reports from Google Drive for analysis.\n",
        "- **Prompt Engineering**: Create structured prompts that direct the LLM to score and justify ESG themes.\n",
        "- **Model Execution and Interpretation**: Run the prompt and assess the model's output, considering accuracy, limitations, and potential biases.\n",
        "- **Exploration**: Experiment with different models, prompts, or reports to observe variation in results.\n",
        "- **Comparison with Traditional Methods**: Use traditional methods, such as sentiment analysis, as a comparison baseline.\n",
        "- **Critical Reflection**: Respond to critical questions on the implications, ethics, and limitations of using AI as a semantic tool for automated ESG analysis.\n",
        "\n"
      ],
      "metadata": {
        "id": "Y0V5kYi7fDme"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Environment Setup\n",
        "\n",
        "Before conducting semantic analysis with Google Gemini, you will need to configure your programming environment. This section installs the necessary Python libraries, sets up your Gemini API credentials, and mounts Google Drive so you can load ESG reports in PDF format.\n",
        "\n",
        "These tools support the following core tasks:\n",
        "\n",
        "- Accessing Gemini via the `google-generativeai` library\n",
        "- Reading ESG reports in PDF format\n",
        "- Generating and analyzing structured ESG output from LLM responses\n",
        "- Managing files and data using Google Drive integration in Colab\n",
        "\n",
        "> You will only need to run these setup commands once at the beginning of the notebook."
      ],
      "metadata": {
        "id": "LvjOljbgk4iB"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "collapsed": true,
        "id": "pOYsIs0Vauk4",
        "outputId": "d4340d7e-9064-465b-d762-645a2a589c55"
      },
      "outputs": [
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          "output_type": "stream",
          "name": "stdout",
          "text": [
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          ]
        }
      ],
      "source": [
        "# Install dependencies\n",
        "!pip install -U google-generativeai"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Import required libraries\n",
        "import os\n",
        "import google.generativeai as genai"
      ],
      "metadata": {
        "id": "I7GILqAzbBvv"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Configure access to Google Gemini API\n",
        "genai.configure(api_key='')  # Replace with your own API Key -- you can apply for a Gemini API key from Google"
      ],
      "metadata": {
        "id": "q102MzMimDGj"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Mount Google Drive so PDFs stored there can be read\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "upRPVxxVbWKV",
        "outputId": "3edf9fd0-00ab-4290-c591-4c25a0f836dd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Step 1: Load Corporate ESG Report (PDF)\n",
        "\n",
        "In this step, you will load a corporate sustainability report in PDF format. This document will serve as the input for Gemini’s semantic ESG analysis.\n",
        "\n",
        "The ESG report should be stored in your Google Drive and represent a real company, preferably one engaged in urban digital twin technologies. You may use a U.S.-based or China-based company depending on your comparative focus.\n",
        "\n",
        " > Gemini will analyze the full text of the PDF and generate structured ESG insights across several environmental, social, and governance themes/criteria."
      ],
      "metadata": {
        "id": "gutoSbZKm7pJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Define the PDF file path of the ESG report you want Gemini to analyze\n",
        "pdf_path = \" \""
      ],
      "metadata": {
        "id": "b-uV00Kuwc0l"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Read the PDF content\n",
        "with open(pdf_path, \"rb\") as f:\n",
        "    pdf_content = f.read()"
      ],
      "metadata": {
        "id": "de8cwla9bSZX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Instantiate the Gemini 2.0 flash model\n",
        "model = genai.GenerativeModel(\"gemini-2.0-flash\")"
      ],
      "metadata": {
        "id": "F97zVC3rb455"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Perform a sanity check -- ask for a brief summary to ensure the PDF was processed correctly\n",
        "summary_response = model.generate_content(\n",
        "    [\n",
        "        {\"text\": \"a summary of the report\"},\n",
        "        {\"mime_type\": \"application/pdf\", \"data\": pdf_content},\n",
        "    ]\n",
        ")\n",
        "print(summary_response.text)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 645
        },
        "id": "DUyrpiOTp6SI",
        "outputId": "313ffd1e-c4ce-47c9-e7cb-9b6b70eb2910"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Here's a summary of the NVIDIA Sustainability Report Fiscal Year 2024, based on the text provided:\n",
            "\n",
            "**Overall Focus:**\n",
            "*   NVIDIA emphasizes its commitment to sustainability, driven by its role in accelerated computing and generative AI. The report highlights the potential of these technologies to reshape industries, enhance efficiency, and address environmental challenges.\n",
            "\n",
            "**Key Areas and Goals:**\n",
            "\n",
            "*   **Climate and Efficiency:**\n",
            "    *   Reducing energy consumption and greenhouse gas (GHG) emissions is a central focus.\n",
            "    *   Targets include achieving 100% renewable electricity for global offices and data centers by the end of fiscal year 2025, and increasing use of GPU-accelerated systems to save energy.\n",
            "    *   It also focuses on reducing emissions by engaging manufacturing suppliers to adopt science-based targets.\n",
            "*   **People, Diversity, and Inclusion:**\n",
            "    *   NVIDIA commits to building a diverse and inclusive workforce.\n",
            "    *   Emphasis on initiatives to attract, retain, and support employees from underrepresented groups in technology.\n",
            "    *   Commitment to pay equity and transparent compensation practices.\n",
            "*   **Responsible Sourcing:**\n",
            "    *   Efforts to ensure responsible sourcing of minerals and materials in the supply chain.\n",
            "    *   Working with suppliers to respect human rights and avoid contributing to conflict.\n",
            "*   **Product Environmental Impact:**\n",
            "    *   Reducing the environmental impact of products through design, manufacturing, packaging, and end-of-life management.\n",
            "    *   Increase use of recycled and recyclable materials.\n",
            "*   **Trustworthy AI:** NVIDIA is committed to developing and deploying AI technologies ethically and responsibly. It is working to ensure fairness, privacy, transparency, and accountability in AI systems.\n",
            "\n",
            "**Key Initiatives and Examples:**\n",
            "*   **Accelerated Computing:** NVIDIA GPUs offer higher energy efficiency than traditional CPUs for AI and HPC workloads, reducing energy consumption and costs.\n",
            "*   **Earth-2 Platform:** NVIDIA's digital twin of Earth helps predict weather patterns and contributes to climate research.\n",
            "*   **AI Applications:** NVIDIA's technology aids in drug discovery, battery development, grid optimization, and reducing waste in various industries.\n",
            "*   **Partnerships:** NVIDIA works with organizations and researchers worldwide to address sustainability challenges.\n",
            "\n",
            "**Governance:**\n",
            "*   Sustainability is overseen by the Nominating and Corporate Governance (NCG) Committee of the Board of Directors and the Corporate Sustainability Steering (CSS) Committee.\n",
            "*   NVIDIA provides metrics related to environmental, social, and governance issues.\n",
            "\n",
            "In essence, the report underscores NVIDIA's commitment to integrating sustainability into its business strategy and contributing to a more sustainable future through its technology and operations. It highlights specific initiatives and targets across various areas of sustainability.\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Step 2: Prompt Engineering\n",
        "\n",
        "In this step, you will craft and apply a structured prompt that directs Gemini to evaluate a company’s ESG disclosure based on the content of its PDF report.\n",
        "\n",
        "Prompt engineering is critical to how effectively the model interprets nuanced sustainability language, assigns scores, and generates meaningful justifications.\n",
        "\n",
        "> In early trials, generic or loosely-worded prompts led to:\n",
        "> - Overgeneralized responses with little differentiation between ESG themes\n",
        "> - Missing or incomplete justifications\n",
        "> - Inconsistent formatting or lack of structure\n",
        "> - Hallucinated claims not present in the actual report\n",
        "\n",
        "To address these issues, the final version of the prompt includes:\n",
        "\n",
        "- A defined list of ESG criteria to be scored\n",
        "- A standardized scoring rubric (0–5) for each item\n",
        "- Instructions for brief justifications tied to specific content\n",
        "- A clear table output format: Category, Item, Score, Justification\n",
        "\n",
        "### Prompt Design Guidelines\n",
        "\n",
        "- Be specific: Name each ESG subcategory you want scored (e.g., carbon neutrality, risk transparency).\n",
        "- Include scoring rules (e.g., 0 = not mentioned, 5 = strong and explicit emphasis).\n",
        "- Request justifications: This improves transparency and interpretability.\n",
        "- Define the output format: Tables are clearer and easier to analyze.\n",
        "\n",
        "### Your Task\n",
        "\n",
        "Use the prompt below or modify it to suit your goals. Then feed it to Gemini along with your ESG report PDF.\n",
        "\n",
        "- Does the model follow the structure?\n",
        "- Are the justifications coherent and grounded in the text?\n",
        "- Are any scores surprising, vague, or unjustified?\n"
      ],
      "metadata": {
        "id": "DVoQ_1M2n6A6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Example prompt\n",
        "prompt = '''\n",
        "\n",
        "You are an ESG analyst.\n",
        "\n",
        "Please read the entire following ESG report (attached as a PDF), and rate the company's commitment and emphasis across key ESG themes.\n",
        "For each item below, assign a score from 0 to 5 on a Likert scale:\n",
        "0 = Not mentioned\n",
        "1 = Mentioned briefly\n",
        "3 = Moderately emphasized\n",
        "5 = Strong and explicit emphasis\n",
        "\n",
        "Also provide a brief justification (1–2 sentences) for each score.\n",
        "\n",
        "Environmental (E):\n",
        " - Carbon neutrality or climate pledges\n",
        " - Use of measurable, time-bound environmental goals\n",
        " - Emphasis on technology and innovation for sustainability\n",
        "Social (S):\n",
        " - Diversity, equity, and inclusion (DEI) focus\n",
        " - Community engagement and small business support\n",
        " - Stakeholder participation or employee empowerment\n",
        "Governance (G):\n",
        " - Risk and compliance transparency\n",
        " - Corporate governance structure and oversight\n",
        " - Ethical standards and trust-building.\n",
        "\n",
        "Return your output in a table format with columns: Category, Item, Score, and Justification.\n",
        "'''"
      ],
      "metadata": {
        "id": "BaHjYK8Tx7uC"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Step 3: Model Execution and Interpretation\n",
        "\n",
        "Now that your prompt and ESG report are ready, it is time to run the Gemini model and evaluate how it scores and explains the company's ESG disclosures.\n",
        "\n",
        "In this step, you will pass both the structured prompt and the full PDF document to Gemini and review the generated output. The model should return a table of scores along with brief justifications for each ESG criterion.\n",
        "\n",
        "> This demonstrates how natural language can facilitate both:\n",
        "> - Structured semantic evaluation of sustainability content\n",
        "> - Interpretive reasoning about a company’s ESG commitments"
      ],
      "metadata": {
        "id": "vi8MxzwhsF7Y"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Run the model\n",
        "response = model.generate_content(\n",
        "    [\n",
        "        {\"text\": prompt},\n",
        "        {\"mime_type\": \"application/pdf\", \"data\": pdf_content},\n",
        "    ]\n",
        ")\n",
        "print(response.text)"
      ],
      "metadata": {
        "id": "8HpoNzTexbyt",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "outputId": "59b85694-4e26-4ec6-bd0f-565d604f0891"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Okay, I have reviewed the provided NVIDIA Sustainability Report Fiscal Year 2024 and will rate the company's commitment and emphasis across the key ESG themes as you requested.\n",
            "\n",
            "Here is the table:\n",
            "\n",
            "| Category | Item | Score | Justification |\n",
            "|---|---|---|---|\n",
            "| Environmental (E) | Carbon neutrality or climate pledges | 5 | The report explicitly states a commitment to 100% renewable electricity for offices and data centers by FY25 and engages suppliers in science-based targets. There is a major emphasis on reducing energy consumption through their products. |\n",
            "| Environmental (E) | Use of measurable, time-bound environmental goals | 5 |  The report includes specific targets such as achieving 100% renewable energy by FY25 and engaging manufacturing suppliers by FY26, with defined scopes (Scope 1, 2, and 3 emissions). |\n",
            "| Environmental (E) | Emphasis on technology and innovation for sustainability | 5 | NVIDIA heavily emphasizes the role of accelerated computing and AI in driving sustainability through energy efficiency improvements, digital twins for climate prediction (Earth-2), and advancements in battery technology. |\n",
            "| Social (S) | Diversity, equity, and inclusion (DEI) focus | 5 | The report features detailed information about DEI initiatives, employee demographics, pay equity analyses, and community resource groups with goals to promote diverse and inclusive recruiting. |\n",
            "| Social (S) | Community engagement and small business support | 3 | The report mentions community resource groups and support for local programs. There is some discussion of the societal impact of their technology.  However, this isn't a central theme, but it exists. |\n",
            "| Social (S) | Stakeholder participation or employee empowerment | 3 | The report describes employee surveys, suggestion boxes, career coaching, and mentorship programs.  While it mentions these, the focus isn't necessarily on *empowerment* but more on talent development and gathering feedback. |\n",
            "| Governance (G) | Risk and compliance transparency | 5 | The report transparently details their risk management and compliance processes, including details about their speak up line and auditing processes, cybersecurity policies, investigation processes, and anti-corruption policies, offering evidence of a strong focus. |\n",
            "| Governance (G) | Corporate governance structure and oversight | 5 | The report highlights the role of the Board of Directors, Corporate Sustainability Steering Committee, and Nominating and Corporate Governance Committee in overseeing sustainability strategy and initiatives. |\n",
            "| Governance (G) | Ethical standards and trust-building | 5 | The report underlines ethical standards throughout the organization, including NVIDIA's Code of Conduct. The report has sections regarding trustworthy AI and their commitment to human rights. |\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Analyze the Output\n",
        "\n",
        "Once Gemini generates a response:\n",
        "\n",
        "- Check formatting: Is the table clear? Are all fields (Category, Item, Score, Justification) present?\n",
        "- Evaluate coherence: Do the justifications seem grounded in the report? Are they vague, generic, or overly confident?\n",
        "- Spot inconsistencies: Did Gemini overlook a theme that was strongly emphasized in the report or highlight something barely mentioned?\n",
        "\n",
        "A key feature of LLMs is that in addition to scoring, they can also reflect. Consider asking Gemini follow-up questions like:\n",
        "\n",
        "- What content led you to assign a low score for DEI?\n",
        "- Which ESG category received the strongest overall emphasis?\n",
        "- What areas does this company underperform in, and why?\n",
        "\n",
        "This tests whether the model understands the context of its own output and can support explainability, which is a key concern in AI-centered sustainability analysis."
      ],
      "metadata": {
        "id": "AmjmA1LgvZmZ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Step 4: Extended Visualizations\n",
        "\n",
        "In this step, you will transform Gemini’s textual output into visual representations such as bar charts or heatmaps. Visualization can help you quickly identify patterns, compare ESG performance across categories, and communicate your findings more clearly.\n",
        "\n",
        "> Below are a few examples of useful visualizations. Consider exploring different visualizations or even comparing the graphs for multiple companies."
      ],
      "metadata": {
        "id": "fYSe222JwaPS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Example DataFrame (replace with parsed Gemini output)\n",
        "\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "data = {\n",
        "    \"Category\": [\"Environmental\", \"Environmental\", \"Environmental\",\n",
        "                 \"Social\", \"Social\", \"Social\",\n",
        "                 \"Governance\", \"Governance\", \"Governance\"],\n",
        "    \"Item\": [\n",
        "        \"Carbon neutrality\", \"Time-bound goals\", \"Innovation for sustainability\",\n",
        "        \"DEI\", \"Community engagement\", \"Stakeholder participation\",\n",
        "        \"Risk transparency\", \"Governance structure\", \"Ethical standards\"\n",
        "    ],\n",
        "    \"Score\": [3, 4, 5, 5, 3, 3, 4, 3, 5]\n",
        "}\n",
        "df = pd.DataFrame(data)\n",
        "\n",
        "# Plot\n",
        "plt.figure(figsize=(10, 6))\n",
        "bars = plt.barh(df[\"Item\"], df[\"Score\"], color=\"turquoise\")\n",
        "plt.xlabel(\"Score (0–5)\")\n",
        "plt.title(\"ESG Theme Scores from Gemini Output\")\n",
        "plt.gca().invert_yaxis()  # Highest score at the top\n",
        "plt.grid(axis=\"x\", linestyle=\"--\", alpha=0.7)\n",
        "plt.tight_layout()\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 599
        },
        "id": "KQpJmul7w3lJ",
        "outputId": "95e5a1e9-1436-44b9-db1d-2abab0a824d1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Example heatmap\n",
        "\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "heatmap_data = df.pivot(index=\"Category\", columns=\"Item\", values=\"Score\")\n",
        "\n",
        "\n",
        "plt.figure(figsize=(12, 5))\n",
        "sns.heatmap(heatmap_data, annot=True, cmap=\"autumn\", cbar_kws={\"label\": \"Score\"})\n",
        "plt.title(\"Heatmap of ESG Emphasis by Theme\")\n",
        "plt.xticks(rotation=45, ha=\"right\")\n",
        "plt.tight_layout()\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 457
        },
        "id": "zfIEWLrmy0qI",
        "outputId": "294493df-6530-4e6f-ee28-967641ffb9ee"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Example radar chart\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "\n",
        "avg_scores = df.groupby(\"Category\")[\"Score\"].mean().reindex([\"Environmental\", \"Social\", \"Governance\"])\n",
        "\n",
        "labels = avg_scores.index.tolist()\n",
        "values = avg_scores.values.tolist()\n",
        "values += values[:1]\n",
        "\n",
        "angles = np.linspace(0, 2 * np.pi, len(labels), endpoint=False).tolist()\n",
        "angles += angles[:1]\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(6, 6), subplot_kw=dict(polar=True))\n",
        "ax.plot(angles, values, linewidth=2, linestyle='solid', color='darkorange')\n",
        "ax.fill(angles, values, alpha=0.25, color='orange')\n",
        "\n",
        "ax.set_yticks(range(0, 6))\n",
        "ax.set_yticklabels(map(str, range(0, 6)))\n",
        "ax.set_xticks(angles[:-1])\n",
        "ax.set_xticklabels(labels)\n",
        "ax.set_title(\"Average ESG Scores by Category\", size=14, pad=20)\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 541
        },
        "id": "pMRhopfyzxNk",
        "outputId": "cdfc26c8-4ac5-4e25-d8cd-df3cf6f2bae8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Example dot plot\n",
        "\n",
        "plt.figure(figsize=(8, 6))\n",
        "sns.stripplot(\n",
        "    data=df,\n",
        "    x=\"Score\",\n",
        "    y=\"Item\",\n",
        "    hue=\"Category\",\n",
        "    palette=\"Set2\",\n",
        "    size=10,\n",
        "    jitter=False\n",
        ")\n",
        "plt.title(\"ESG Scores per Theme\")\n",
        "plt.xlabel(\"Score (0–5)\")\n",
        "plt.legend(title=\"Category\", bbox_to_anchor=(1.05, 1), loc='upper left')\n",
        "plt.tight_layout()\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 607
        },
        "id": "pJ4_xIjKz_Vs",
        "outputId": "c26a5670-9693-4011-fe65-542a36beafd8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ],
            "image/png": 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rq4u1atUSR44cKT558kShjKenp+jg4FBkTNnZ2eKSJUtEBwcHqZ+mTZuKc+bMEdPT00VRFMXQ0FDRx8dHrF27tqihoSHWrl1b7NevX6HbfBYFgDh69Gjx119/FW1sbERNTU3RxcVFDAsLK1T2wYMH4ujRo0Vzc3NRXV1dNDExEdu1aydu2rRJKlNwm9Ndu3aV2vfrlLnNaZcuXQrt9/T0FD09PRX2PXv2TJw6dapobW0tamhoiDVq1BDd3d3FZcuWSbetLbjN6ffff69Qt7hzKPjsnj9/vlB5Ly8v0cDAQNTS0hLr168v+vn5Kdw6lohIWYIoKjnuTURE9BYIgoDRo0fzl24ioiqCaxCIiIiIiEjCBIGIiIiIiCRMEIiIiIiISMK7GBERUaXiUjgioqqFIwhERERERCRhgkBERERERBJOMSKqwuRyOf777z/o6elBEITKDoeI6KMniiKePXuG2rVrQ0WFv7PSh4kJAlEV9t9//8Hc3LyywyAiotckJSWhTp06lR0G0VvBBIGoCtPT0wOQ/z8ifX39So6GiIiePn0Kc3Nz6e8z0YeICQJRFVYwrUhfX58JAhFRFcJpn/Qh4+Q5IiIiIiKSMEEgIiIiIiIJEwQiIiIiIpJwDQIRERFRFZWXl4ecnJzKDoM+AOrq6lBVVVWqLBMEIiIioipGFEXcv38faWlplR0KfUAMDQ1hYmJS6iJ7JghEREREVUxBclCzZk3o6Ojwrkn0RkRRRGZmJh4+fAgAMDU1LbE8EwQiIiKiKiQvL09KDqpXr17Z4dAHQltbGwDw8OFD1KxZs8TpRlykTERERFSFFKw50NHRqeRI6ENT8JkqbV0LEwQiIiKiKojTiqiiKfuZYoJAREREREQSJghERERERCRhgkBEREREFeL+/fsYO3YsrKysoKmpCXNzc3h7eyM0NFSp+kFBQTA0NHy7QVKpeBcjIiIiInpjCQkJ8PDwgKGhIb7//ns4OjoiJycHR44cwejRo3H9+vXKDrHMcnJyoK6uXtlhvHMcQSAiIiKiNzZq1CgIgoCIiAj07NkTDRo0gIODA7799lv8888/AIDly5fD0dERurq6MDc3x6hRo5CRkQEAOHHiBAYNGoT09HQIggBBEDB79mwAQFZWFvz9/WFmZgZdXV00b94cJ06cUOj/xx9/hLm5OXR0dNCjRw8sX7680GjE+vXrUb9+fWhoaMDW1hZbt25VOC4IAtavX49u3bpBV1cX8+fPh7W1NZYtW6ZQLioqCoIg4NatWxV3AasQJghERERE9EZSU1MREhKC0aNHQ1dXt9Dxgi/qKioqWLVqFa5evYotW7bgr7/+wqRJkwAA7u7uWLlyJfT19ZGcnIzk5GT4+/sDAMaMGYOzZ89ix44duHz5Mnr16oWOHTvi5s2bAIDw8HCMGDEC48ePR1RUFDp06IAFCxYoxLB3716MHz8eEydOxJUrVzB8+HAMGjQIYWFhCuVmz56NHj16ICYmBkOGDMHgwYMRGBioUCYwMBCtWrWCtbV1hVy/KkckoiorPT1dBCCmp6dXdihERCS+m7/LL168EK9duya+ePHirfVR0c6dOycCEPfs2VOmert27RKrV68ubQcGBooGBgYKZe7evSuqqqqK9+7dU9jfrl07cerUqaIoimKfPn3ELl26KBz39fVVaMvd3V0cNmyYQplevXqJnTt3lrYBiBMmTFAoc+/ePVFVVVU8d+6cKIqimJ2dLdaoUUMMCgoq07lWBcp+tjiCQERERERvRBRFpcodP34c7dq1g5mZGfT09NC/f3+kpKQgMzOz2DoxMTHIy8tDgwYNIJPJpNfJkydx+/ZtAEBcXBzc3NwU6r2+HRsbCw8PD4V9Hh4eiI2NVdjn6uqqsF27dm106dIFmzdvBgD8+eefyMrKQq9evZQ65/cRFykTERER0RuxsbGBIAglLkROSEhA165dMXLkSCxYsADVqlXD6dOnMWTIEGRnZxf75OiMjAyoqqri4sWLUFVVVTgmk8kq9DwAFDlFaujQoejfvz9WrFiBwMBA9OnT54N+0jUTBKIP2JOsTMSm3cfL3BxoqanDztAERpof7h80IiKqHNWqVYOXlxfWrl2LcePGFfqSnZaWhosXL0IulyMgIAAqKvmTWH7//XeFchoaGsjLy1PY5+Ligry8PDx8+BAtW7Yssn9bW1ucP39eYd/r23Z2dggPD8fAgQOlfeHh4bC3ty/1/Dp37gxdXV2sX78eISEh+Pvvv0ut8z5jgkD0AUp4loLDSVdxOfUe5K8M+6oIApyqmaGTuQMs9apXYoRERPShWbt2LTw8PODm5oa5c+fCyckJubm5OHbsGNavX48dO3YgJycHq1evhre3N8LDw7FhwwaFNiwtLZGRkYHQ0FA4OztDR0cHDRo0gK+vLwYMGICAgAC4uLjg0aNHCA0NhZOTE7p06YKxY8eiVatWWL58Oby9vfHXX3/h8OHDEARBavu7775D79694eLigvbt2+PPP//Enj17cPz48VLPTVVVFX5+fpg6dSpsbGzQokWLCr9+VQnXIHzE/Pz80L1798oO471x4sQJCIKAtLQ0AFX3YS6Rj5PwffQxRKX8q5AcAIBcFBGV8m/+8cdJlRQhERF9iKysrHDp0iW0adMGEydORKNGjdChQweEhoZi/fr1cHZ2xvLly7FkyRI0atQI27Ztw6JFixTacHd3x4gRI9CnTx8YGxtj6dKlAPLvGjRgwABMnDgRtra26N69O86fPw8LCwsA+WsJNmzYgOXLl8PZ2RkhISH45ptvoKWlJbXdvXt3/PDDD1i2bBkcHBywceNGBAYGonXr1kqdX8FUqEGDBlXMBavCBFHZVSVUKe7fv48FCxbg4MGDuHfvHmrWrInGjRtjwoQJaNeu3Ru17efnh7S0NOzbt69igq1iEhISUK9ePURGRqJx48Zv3N6JEyfQpk0bPHnyBIaGhnjx4gWePXuGmjVrAsi/Ldq+ffsQFRX1xn0VePr0KQwMDJCeng59ff1Syyc8S8H30ceQK8pLLasmqOA75w4cSSAiKoOy/l0uj5cvX+LOnTuoV6+ewhdcKpthw4bh+vXrOHXqVIW0d+rUKbRr1w5JSUmoVatWhbT5rin72eIUoyrsbT2RMC8vT2HI7WOXnZ0NDQ2NMtfT1taGtrb2W4io/A4nXVUqOQCAXFGOkKRrGGFf9HxOIiKi98myZcvQoUMH6Orq4vDhw9iyZQvWrVv3xu1mZWXh0aNHmD17Nnr16vXeJgdlwSlGVZgyTyQESn4qIfC/qTDBwcGwt7eHpqYmEhMTpeNz5syBsbEx9PX1MWLECGRnZ0vHsrKyMG7cONSsWRNaWlr49NNPFRb9FEy7CQ0NhaurK3R0dODu7o64uLhizyshIQGCIGDPnj1o06YNdHR04OzsjLNnzyqUO336NFq2bAltbW2Ym5tj3LhxeP78uXRcEIRCox+GhoYICgoCANSrVw9A/uImQRCkIcSCqVULFixA7dq1YWtrCwDYunUrXF1doaenBxMTE3z55Zd4+PBhsefx6hSjoKAgzJkzB9HR0dLTH4OCgjB48GB07dpVoV5OTg5q1qyJn3/+udi2y+NJViYup9wrU53o1H/xJKv4W8sRERG9LyIiItChQwc4Ojpiw4YNWLVqFYYOHfrG7W7fvh1169ZFWlqaNOXpQ8cEoYpS9omEQMlPJSyQmZmJJUuW4KeffsLVq1elaTGhoaGIjY3FiRMnsH37duzZswdz5syR6k2aNAm7d+/Gli1bcOnSJVhbW8PLywupqakK7U+bNg0BAQG4cOEC1NTUMHjw4FLPcdq0afD390dUVBQaNGiAfv36ITc3FwBw+/ZtdOzYET179sTly5exc+dOnD59GmPGjFH6GkZERADIv+dycnIy9uzZIx0LDQ1FXFwcjh07hgMHDgDI/+I+b948REdHY9++fUhISICfn59SffXp0wcTJ06Eg4OD9PTHPn36YOjQoQgJCUFycrJU9sCBA8jMzESfPn0KtZOVlYWnT58qvJQVm3YfcpRtxqBcFHE97X6Z6hAREVVFv//+Ox4+fIgXL17g6tWrGDFiRIW06+fnh7y8PFy8eBFmZmYV0mZVxwShirp16xZEUUTDhg1LLTthwgS0adMGlpaWaNu2LebPn1/otmE5OTlYt24d3N3dYWtrK927V0NDA5s3b4aDgwO6dOmCuXPnYtWqVZDL5Xj+/DnWr1+P77//Hp06dYK9vT1+/PFHaGtrF/r1e8GCBfD09IS9vT2mTJmCM2fO4OXLlyXG7e/vjy5duqBBgwaYM2cO7t69i1u3bgEAFi1aBF9fX0yYMAE2NjZwd3fHqlWr8Msvv5TabgFjY2MAQPXq1WFiYoJq1apJx3R1dfHTTz/BwcEBDg4OAIDBgwejU6dOsLKywieffIJVq1bh8OHDCqMxxdHW1oZMJoOamhpMTExgYmICbW1t6Xpv3bpVKhsYGIhevXoVee/mRYsWwcDAQHqZm5srda4A8DI3R+myr3pRznpERET0YWKCUEWVZe24Mk8l1NDQgJOTU6G6BbcQK9CiRQtkZGQgKSkJt2/fRk5OjsJTB9XV1eHm5lboqYOvtm1qagoAJU7PKa1OdHQ0goKCFJ6Y6OXlBblcjjt37pR6TUrj6OhYaN3BxYsX4e3tDQsLC+jp6cHT0xMAFKZjlcfQoUMRGBgIAHjw4AEOHz5c7AjL1KlTkZ6eLr2SkpS/05CWmnq54tMuZz0iIiL6MDFBqKKUeSIh8L+nEjo5OWH37t24ePEi1q5dCwAKawm0tbXf6sJkdfX/fcks6EcuL3mxbEl1MjIyMHz4cERFRUmv6Oho3Lx5E/Xr15fqvJ5I5eQo92v469O2nj9/Di8vL+jr62Pbtm04f/489u7dC0DxOpbHgAEDEB8fj7Nnz+LXX39FvXr1in3Qi6amJvT19RVeyrIzNIFKGd9jFUFAQ0OTMtUhIiKiDxvvYlRFKfNEQkNDQ6WeSliS6OhovHjxQrobzz///AOZTAZzc3PUqFEDGhoaCA8PR926dQHkfwE/f/48JkyYUDEnWowmTZrg2rVrsLa2LraMsbGxwtz+mzdvFho1AVDoiYxFuX79OlJSUrB48WJpWs+FCxfKFHNRT38E8qc4de/eHYGBgTh79uxbu3+ykaYOnKqZISrlX6XrOFerwycrExERkQKOIFRha9euRV5eHtzc3LB7927cvHkTsbGxWLVqlfQEP2tra+mphPHx8di6dWuhpxKWJDs7G0OGDMG1a9dw6NAhzJo1C2PGjIGKigp0dXUxcuRIfPfddwgJCcG1a9cwbNgwZGZmYsiQIW/rtAEAkydPxpkzZzBmzBhERUXh5s2b2L9/v8Ii5bZt22LNmjWIjIzEhQsXMGLECIVRiZo1a0JbWxshISF48OAB0tPTi+3PwsICGhoa0nUMDg7GvHnzyhSzpaUl7ty5g6ioKDx+/BhZWVnSsaFDh2LLli2IjY1VeMR7Retk7gA1Qbl/1uoqquhoXvrj5YmIiOjjwgShCivtiYQAlHoqYUnatWsHGxsbtGrVCn369EG3bt0we/Zs6fjixYvRs2dP9O/fH02aNMGtW7dw5MgRGBkZVfTpKnBycsLJkydx48YNtGzZEi4uLpg5cyZq164tlQkICIC5uTlatmyJL7/8Ev7+/grrKdTU1LBq1Sps3LgRtWvXho+PT7H9GRsbIygoCLt27YK9vT0WL16MZcuWlSnmnj17omPHjmjTpg2MjY2xfft26Vj79u1hamoKLy8vhXOoaJZ61TGsoUepSYKaoIKhtu58SBoR0QfsSVYmzjyIx1/34nDmQTxva01K45OUid6BjIwMmJmZITAwEJ9//rnS9cr7xM6EZykISbqG6NR/IX/ln7iKIMC5Wh10NLdnckBEVA7vw5OUE56l4HDSVVxOvVfo/wFO1czQydzhvf5/gCAI2Lt3L7p3717ZoVQ5s2fPxr59+xAVFVXkcT5JmagKkMvlePz4MQICAmBoaIhu3bq9k34t9apjhH1LPMnKxPW0+3iRmwNtNXU0NDThmgMiog9Y5OMk/HQ9HLli4RuFyEURUSn/4krqfxjW0AONayh/K21l+fn5YcuWLYX2e3l5ISQkpEL6SE5OfuszGSqbn58f0tLSCj0Q9l1hgkD0FiUmJqJevXqoU6cOgoKCoKb2bv/JGWnqoEUtq3faJxERVY6EZynFJgevyhXl+PF6OL5z7vBWRhI6duwo3d67gKamZoW1b2JS8t33cnJyFNYkUtlxDQLRW2RpaQlRFJGUlIR27dpVdjhERPQBO5x0tdTkoECuKEdI0rW3Eoempqb00NCCV8Ev/oIg4KeffkKPHj2go6MDGxsbBAcHA8gfda9Tp460zrJAZGQkVFRUcPfuXamNgl/WExISIAgCdu7cCU9PT2hpaWHbtm2Qy+WYO3cu6tSpA01NTTRu3FhhBKOg3p49e9CmTRvo6OjA2dkZZ8+elcoEBQXB0NAQBw4ckB4y+8UXXyAzMxNbtmyBpaUljIyMMG7cOIW7GGZlZcHf3x9mZmbQ1dVF8+bNceLEiULtHjlyBHZ2dpDJZOjYsaN0Z8bZs2djy5Yt2L9/PwRBgCAIUv3JkyejQYMG0NHRgZWVFWbMmKH0Ld7LggkCERER0XvuSVYmLqfcK1Od6NR/K2Xh8pw5c9C7d29cvnwZnTt3hq+vL1JTU6GiooJ+/frht99+Uyi/bds2eHh4SLdcL8qUKVMwfvx4xMbGwsvLCz/88AMCAgKwbNkyXL58GV5eXujWrRtu3rypUG/atGnw9/dHVFQUGjRogH79+iE3N1c6npmZiVWrVmHHjh0ICQnBiRMn0KNHDxw6dAiHDh3C1q1bsXHjRvzxxx9SnTFjxuDs2bPYsWMHLl++jF69eqFjx44KfWdmZmLZsmXYunUr/v77byQmJsLf3x8A4O/vj969e0tJQ3JyMtzd3QEAenp6CAoKwrVr1/DDDz/gxx9/xIoVK8r/ZhSDCQIRERHRey427T7kKNt9Z+SiiOtp9ys8lgMHDkAmkym8Fi5cKB338/NDv379YG1tjYULFyIjIwMREREAAF9fX4SHhyMxMTE/RrkcO3bsgK+vb4l9TpgwAZ9//jnq1asHU1NTLFu2DJMnT0bfvn1ha2uLJUuWoHHjxli5cqVCPX9/f3Tp0gUNGjTAnDlzcPfuXdy6dUs6npOTg/Xr18PFxQWtWrXCF198gdOnT+Pnn3+Gvb09unbtijZt2iAsLAxA/tTiwMBA7Nq1Cy1btkT9+vXh7++PTz/9VGHaVU5ODjZs2ABXV1c0adIEY8aMQWhoKABAJpNBW1tbYSSm4NlO06dPh7u7OywtLeHt7Q1/f/8yPf9KWVyDQERERPSee5lbvmkmL8pZryRt2rQpNE2oWrVq0n87OTlJ/62rqwt9fX08fPgQANC4cWPY2dnht99+w5QpU3Dy5Ek8fPgQvXr1KrFPV1dX6b+fPn2K//77Dx4eHgplPDw8EB0drbDv1VhMTU0BAA8fPkTDhg0BADo6Oqhfv75UplatWrC0tIRMJlPYVxB/TEwM8vLy0KBBA4V+srKyUL36/9Z7vN6uqamp1EZJdu7ciVWrVuH27dvIyMhAbm7uW7mbFhMEIiIiovecllr5FuVql7NeSXR1dWFtbV3s8dcXEAuCALn8f2snfH19pQTht99+Q8eOHRW+XBfXZ3m8GosgCACgEEtRsZYUf0ZGBlRVVXHx4kWoqqoqlHs1qSiqjdKePHD27Fn4+vpizpw58PLygoGBAXbs2IGAgIDSTrPMmCAQERERvefsDE2gIggKzz0ojYogoKFhyXcEqgxffvklpk+fjosXL+KPP/7Ahg0bylRfX18ftWvXRnh4ODw9PaX94eHhcHNzq+hwFbi4uCAvLw8PHz5Ey5Yty92OhoaGwsJnADhz5gzq1q2LadOmSfsKFm5XNCYIRERERO85I00dOFUzQ1TKv0rXca5W5608GycrKwv37yuubVBTU0ONGjWUqm9paQl3d3cMGTIEeXl55XqG0HfffYdZs2ahfv36aNy4MQIDAxEVFYVt27aVua2yaNCgAXx9fTFgwAAEBATAxcUFjx49QmhoKJycnNClSxel2rG0tMSRI0cQFxeH6tWrw8DAADY2NkhMTMSOHTvQrFkzHDx4EHv37n0r58FFykREREQfgE7mDlATlPtqp66iio7m9m8ljpCQEJiamiq8Pv300zK14evri+joaPTo0QPa2tpljmHcuHH49ttvMXHiRDg6OiIkJATBwcGwsbEpc1tlFRgYiAEDBmDixImwtbVF9+7dcf78eVhYWCjdxrBhw2BrawtXV1cYGxsjPDwc3bp1wzfffIMxY8agcePGOHPmDGbMmPFWzkEQS5vwRESV5unTpzAwMEB6evpbWYRERERl8y7+Lr98+RJ37txBvXr1oKWlVaa6UY+T8GMpD0tTE1Te2pOUqWpT9rPFEQQiIiKiD0TjGub4zrkDXKqbQ+X/L7otoCIIcKmef5zJAZWEaxCIiIiIPiCWetUxwr4lnmRl4nrafbzIzYG2mjoaGpq8lTUH9OFhgkBERET0ATLS1EGLWlaVHQa9hzjFiIiIiIiIJEwQiIiIiIhIwgSBiIiIiIgkTBCIiIiIiEjCBIGIiIiIiCS8ixERERHRB0h89gRi4lUg6yWgqQXBwgGCnlFlh0XvASYIRERERB8Q8X4C5BEHgfhoQJ73v/0qqoCVM1TcukAwsay8AN+ApaUlJkyYgAkTJihVPigoCBMmTEBaWtpbjetDwylGRERERB8I8eYlyHcuAm5dUkgOAORv38o/Lt669Fb6f/ToEUaOHAkLCwtoamrCxMQEXl5eCA8Pr5D2z58/j6+//rpC2qLicQSBiIiI6AMg3k+A/NBGIC+35IJ5uZAf3AiVPlMrfCShZ8+eyM7OxpYtW2BlZYUHDx4gNDQUKSkpFdK+sbFxhbRDJeMIAhEREdEHQB5xsPTkoEBebn75CpSWloZTp05hyZIlaNOmDerWrQs3NzdMnToV3bp1AwAkJibCx8cHMpkM+vr66N27Nx48eKDQzp9//olmzZpBS0sLNWrUQI8ePaRjlpaWWLlypbS9fPlyODo6QldXF+bm5hg1ahQyMjIq9Lw+RkwQiIiIiN5z4rMnwO2oslWKj86vV0FkMhlkMhn27duHrKysQsflcjl8fHyQmpqKkydP4tixY4iPj0efPn2kMgcPHkSPHj3QuXNnREZGIjQ0FG5ubsX2qaKiglWrVuHq1avYsmUL/vrrL0yaNKnCzuljxSlGRERERO85MfEqIMrLVkmeBzHxGgQHjwqJQU1NDUFBQRg2bBg2bNiAJk2awNPTE3379oWTkxNCQ0MRExODO3fuwNzcHADwyy+/wMHBAefPn0ezZs2wYMEC9O3bF3PmzJHadXZ2LrbPVxcrW1paYv78+RgxYgTWrVtXIef0seIIAhEREdH7Lutl+epll7NeMXr27In//vsPwcHB6NixI06cOIEmTZogKCgIsbGxMDc3l5IDALC3t4ehoSFiY2MBAFFRUWjXrp3S/R0/fhzt2rWDmZkZ9PT00L9/f6SkpCAzM7NCz+tjwwSBiIiI6H2nqVW+ehrlrFcCLS0tdOjQATNmzMCZM2fg5+eHWbNmKVVXW1tb6X4SEhLQtWtXODk5Yffu3bh48SLWrl0LAMjOzi5X7JSPCQIRERHRe06wcABUVMtWSUUVgoX92wnoFfb29nj+/Dns7OyQlJSEpKQk6di1a9eQlpYGe/v8OAqmIinj4sWLkMvlCAgIwCeffIIGDRrgv//+eyvn8LHhGgQiIiKi95ygZwRYOec//0BZVs4V+mTllJQU9OrVC4MHD4aTkxP09PRw4cIFLF26FD4+Pmjfvj0cHR3h6+uLlStXIjc3F6NGjYKnpydcXV0BALNmzUK7du1Qv3599O3bF7m5uTh06BAmT55cqD9ra2vk5ORg9erV8Pb2Rnh4ODZs2FBh5/Mx4wgCERER0QdAxa0LoKrkb7+q6vnlK5BMJkPz5s2xYsUKtGrVCo0aNcKMGTMwbNgwrFmzBoIgYP/+/TAyMkKrVq3Qvn17WFlZYefOnVIbrVu3xq5duxAcHIzGjRujbdu2iIiIKLI/Z2dnLF++HEuWLEGjRo2wbds2LFq0qELP6WMliKIoVnYQRFS0p0+fwsDAAOnp6dDX16/scIiIPnrv4u/yy5cvcefOHdSrVw9aWmVbIyDeugT5wVIelqaqBpUuwyFYN3nDSOl9o+xniyMIRERERB8IwboJVPpMBaybFF6ToKIK/P/jTA6oJFyDQERERPQBEUwsodptNMRnTyAmXsu/lamGFgQL+wpdc0AfLiYIRERERB8gQc+owh6CRh8XTjEiIiIiIiIJEwQiIiIiIpIwQSAiIiIiIgkTBCIiIiIikjBBICIiIiIiCe9iRERERPQBevY8G4nJT5GVkwdNdVVYmOpDT1ejssOi9wATBCIiIqIPyP3HzxERk4z4pHTIRVHaryIIsDI3gJujKUxq6FZihFTVcYoRERG9VU+yMnHmQTz+uheHMw/i8SQrs7JDIvpg3bz7BDsPX8etxDSF5AAA5KKIW4lp///4k7cWw/379zF+/HhYW1tDS0sLtWrVgoeHB9avX4/MTP77fx9wBIGIiN6KhGcpOJx0FZdT7xX6FdOpmhk6mTvAUq96JUZI9GG5//g5Dv0djzy5WGK5PLmIgyfj0adTwwofSYiPj4eHhwcMDQ2xcOFCODo6QlNTEzExMdi0aRPMzMzQrVu3Cu1TWdnZ2dDQ4BQrZXAE4T3k5+eH7t27V0rflpaWWLlyZaX0rQxBELBv377KDgOtW7fGhAkTKjsMokoT+TgJ30cfQ1TKv0X+ihmV8m/+8cdJlRQh0YcnIia51OSgQJ5cRERMcoXHMGrUKKipqeHChQvo3bs37OzsYGVlBR8fHxw8eBDe3t4AgMTERPj4+EAmk0FfXx+9e/fGgwcPAAA3btyAIAi4fv26QtsrVqxA/fr1pe0rV66gU6dOkMlkqFWrFvr374/Hjx9Lx1u3bo0xY8ZgwoQJqFGjBry8vHDixAkIgoDQ0FC4urpCR0cH7u7uiIuLk+rdvn0bPj4+qFWrFmQyGZo1a4bjx48rxGJpaYmFCxdi8ODB0NPTg4WFBTZt2qRQ5t9//0W/fv1QrVo16OrqwtXVFefOnZOO79+/H02aNIGWlhasrKwwZ84c5ObmvuE7UDGYIFQxgiCU+Jo9ezZ++OEHBAUFVXaoRERFSniWgp+uhyNXlJdYLleU48fr4Uh4lvKOIiP6cD17no3bSWllqhOflI5nz7MrLIaUlBQcPXoUo0ePhq5u0SMTgiBALpfDx8cHqampOHnyJI4dO4b4+Hj06dMHANCgQQO4urpi27ZtCnW3bduGL7/8EgCQlpaGtm3bwsXFBRcuXEBISAgePHiA3r17K9TZsmULNDQ0EB4ejg0bNkj7p02bhoCAAFy4cAFqamoYPHiwdCwjIwOdO3dGaGgoIiMj0bFjR3h7eyMxMVGh7YCAALi6uiIyMhKjRo3CyJEjpUQjIyMDnp6euHfvHoKDgxEdHY1JkyZBLs//u3jq1CkMGDAA48ePx7Vr17Bx40YEBQVhwYIF5bn0FY5TjKqY5OT/ZfM7d+7EzJkzFbJamUwGmUxWGaERESnlcNLVUpODArmiHCFJ1zDCvuVbjorow5aY/BSicoMHErkoIjH5KRysa1RIDLdu3YIoirC1tVXYX6NGDbx8+RIAMHr0aLRv3x4xMTG4c+cOzM3NAQC//PILHBwccP78eTRr1gy+vr5Ys2YN5s2bByB/VOHixYv49ddfAQBr1qyBi4sLFi5cKPWzefNmmJub48aNG2jQoAEAwMbGBkuXLpXKFHzPWrBgATw9PQEAU6ZMQZcuXfDy5UtoaWnB2dkZzs7OUp158+Zh7969CA4OxpgxY6T9nTt3xqhRowAAkydPxooVKxAWFgZbW1v89ttvePToEc6fP49q1aoBAKytraW6c+bMwZQpUzBw4EAAgJWVFebNm4dJkyZh1qxZ5XsDKhBHEKoYExMT6WVgYABBEBT2yWSyQlOMWrdujbFjx2LChAkwMjJCrVq18OOPP+L58+cYNGgQ9PT0YG1tjcOHDyv0VdrQXHGePXuGfv36QVdXF2ZmZli7dq3C8ZKGDYGip0hNmDABrVu3VjincePGYdKkSahWrRpMTEwwe/ZshTo3b95Eq1atoKWlBXt7exw7dkyp2H19faGrqwtTU1OsWLGi0HSgJ0+eYMCAATAyMoKOjg46deqEmzdvSsdTUlLQr18/mJmZQUdHB46Ojti+fXuJ/a5btw42NjbSYq0vvvii1FiJ3kdPsjJxOeVemepEp/7LhctEbygrJ69c9bLLWa8sIiIiEBUVBQcHB2RlZSE2Nhbm5uZScgAA9vb2MDQ0RGxsLACgb9++SEhIwD///AMgf/SgSZMmaNiwIQAgOjoaYWFh0g+nMplMOnb79m2p3aZNmxYZk5OTk/TfpqamAICHDx8CyP/139/fH3Z2djA0NIRMJkNsbGyhEYRX2yj4vlbQRlRUFFxcXKTk4HXR0dGYO3euQvzDhg1DcnJylVjIzQThA7FlyxbUqFEDERERGDt2LEaOHIlevXrB3d0dly5dwmeffYb+/ftLHzplh+aK8v3338PZ2RmRkZGYMmUKxo8fL305L23YsKznpKuri3PnzmHp0qWYO3euQj+ff/45NDQ0cO7cOWzYsAGTJ08utc1vv/0W4eHhCA4OxrFjx3Dq1ClcunRJoYyfnx8uXLiA4OBgnD17FqIoonPnzsjJyQEAvHz5Ek2bNsXBgwdx5coVfP311+jfvz8iIiKK7PPChQsYN24c5s6di7i4OISEhKBVq1ZFls3KysLTp08VXkTvk9i0+5CjbD9jykUR19Puv6WIiD4Omuqq5aqnUc56RbG2toYgCAozH4D8X8etra2hra2tdFsmJiZo27YtfvvtNwDAb7/9Bl9fX+l4RkYGvL29ERUVpfAq+PGwQHFTndTV1aX/FgQBAKTpP/7+/ti7dy8WLlyIU6dOISoqCo6OjsjOzi62jYJ2Ctoo7VwzMjIwZ84chdhjYmJw8+ZNaGlplVj3XeAUow+Es7Mzpk+fDgCYOnUqFi9ejBo1amDYsGEAgJkzZ2L9+vW4fPkyPvnkE6WH5ori4eGBKVOmAMifJxgeHo4VK1agQ4cOCA0NLXXYUFlOTk7SMJuNjQ3WrFmD0NBQdOjQAcePH8f169dx5MgR1K5dGwCwcOFCdOrUqdj2nj17hi1btuC3335Du3btAACBgYFSfSB/VCI4OBjh4eFwd3cHkP+rhbm5Ofbt24devXrBzMwM/v7+Up2xY8fiyJEj+P333+Hm5lao38TEROjq6qJr167Q09ND3bp14eLiUmSMixYtwpw5c5S+RkRVzcvcnHLVe1HOekSUz8JUHyqCUOimACVREQRYmOpXWAzVq1dHhw4dsGbNGowdO7bYL+d2dnZISkpCUlKS9F3h2rVrSEtLg729vVTO19cXkyZNQr9+/RAfH4++fftKx5o0aYLdu3fD0tISamoV+3U2PDwcfn5+6NGjB4D8L/MJCQllasPJyQk//fQTUlNTixxFaNKkCeLi4hSmHVUlHEH4QLw6zKWqqorq1avD0dFR2lerVi0A/xs+K21obtu2bQrHTp06JbXVokULhb5btGghDQkqM2xYnnMC8ocAC+Iv6OfVL/evx/W6+Ph45OTkKHyJNzAwUJgrGRsbCzU1NTRv3lzaV716ddja2krx5+XlYd68eXB0dES1atUgk8lw5MiRQkOPBTp06IC6devCysoK/fv3x7Zt24odPpw6dSrS09OlV1IS7/BC7xctNfXSCxVBu5z1iCifnq4GrMwNylTHytygwp+svG7dOuTm5sLV1RU7d+5EbGws4uLi8Ouvv+L69etQVVVF+/bt4ejoCF9fX1y6dAkREREYMGAAPD094erqKrX1+eef49mzZxg5ciTatGmj8P/80aNHIzU1Ff369cP58+dx+/ZtHDlyBIMGDUJe3ptNm7KxscGePXsQFRWF6OhofPnll9LIgLL69esHExMTdO/eHeHh4YiPj8fu3btx9uxZAPk/3P7yyy+YM2cOrl69itjYWOzYsUP6sbeyMUH4QBQ1zFXS8FlpQ3PdunVT2P/qP9g3paKiAvG1XzgKpu+Udk5l/Qf6Nnz//ff44YcfMHnyZISFhSEqKgpeXl6Fhh4L6Onp4dKlS9i+fTtMTU0xc+ZMODs7Iy0trVBZTU1N6OvrK7yI3id2hiZQ+f9/b5SlIghoaGjyliIi+ni4OZpCVUW5f3+qqgLcHE0rPIb69esjMjIS7du3x9SpU+Hs7AxXV1esXr0a/v7+mDdvHgRBwP79+2FkZIRWrVqhffv2sLKyws6dOxXa0tPTg7e3N6KjoxWmFwFA7dq1ER4ejry8PHz22WdwdHTEhAkTYGhoCBWVN/t6u3z5chgZGcHd3R3e3t7w8vJCkyZNytSGhoYGjh49ipo1a6Jz585wdHTE4sWLoaqaP6XLy8sLBw4cwNGjR9GsWTN88sknWLFiBerWrftGsVcUTjH6SCkzNKenp1fk/oIFQ69u29nZAVBu2NDY2BhXrlxRaCMqKqpQQlCSgn6Sk5OlxUWvx/U6KysrqKur4/z587CwsAAApKen48aNG9J8RTs7O+Tm5uLcuXPSFKOUlBTExcVJ8YeHh8PHxwdfffUVgPyk68aNGwrDoq9TU1ND+/bt0b59e8yaNQuGhob466+/8Pnnnyt9zkTvAyNNHThVM0NUyr9K13GuVgdGmjpvMSqij4NJDV108bTCwZMlPyxNVUVAl1ZWFf6QtAKmpqZYvXo1Vq9eXWwZCwsL7N+/v9S2du7cWShxKFDwS39xTpw4UWhf69atC/1I2bhxY4V9lpaW+OuvvxTKjB49WmG7qClHUVFRCtt169bFH3/8UWx8Xl5e8PLyKvZ4ZeIIwkfqTYbmwsPDsXTpUty4cQNr167Frl27MH78eABQatiwbdu2uHDhAn755RfcvHkTs2bNKpQwlKZ9+/Zo0KABBg4ciOjoaJw6dQrTpk0rsY6enh4GDhyI7777DmFhYbh69SqGDBkCFRUVaYTFxsYGPj4+GDZsGE6fPo3o6Gh89dVXMDMzg4+Pj1Tm2LFjOHPmDGJjYzF8+HCFuzS97sCBA1i1ahWioqJw9+5d/PLLL5DL5YVuA0f0oehk7gA1Qbn/vairqKKjefHJNRGVjbWFEfp0aghrC8NCo3kqggBrC8P/f9yokiKk9wEThI/UmwzNTZw4ERcuXICLiwvmz5+P5cuXSxmwMsOGXl5emDFjBiZNmoRmzZrh2bNnGDBgQJniV1FRwd69e/HixQu4ublh6NChSj1cZPny5WjRogW6du2K9u3bw8PDA3Z2dgp3DAgMDETTpk3RtWtXtGjRAqIo4tChQ9IIx/Tp09GkSRN4eXmhdevW0hzD4hgaGmLPnj1o27Yt7OzssGHDBmzfvh0ODg5lOmei94WlXnUMa+hRapKgJqhgqK07LPWqv6PIiD4OJjV00a2NNYb0dISXhyXauJnDy8MSQ3o6olsb67c2ckAfDkF8fZyF6CPy/PlzmJmZISAgAEOGDKnscAp5+vQpDAwMkJ6ezvUI9N5JeJaCkKRriE79V+HOKiqCAOdqddDR3J7JAb133sXf5ZcvX+LOnTuoV69elbjlJX04lP1scQ0CfVQiIyNx/fp1uLm5IT09HXPnzgUAafoQEVUcS73qGGHfEk+yMnE97T5e5OZAW00dDQ1NuOaAiKgKY4JAH51ly5YhLi4OGhoaaNq0KU6dOoUaNSrmMfNEVJiRpg5a1LKq7DCI3juc5EEVTdnPFBME+qi4uLjg4sWLlR0GERFRsQrWvGVmZpbp6cNEpSl4DlNpd45kgkBERERUhaiqqsLQ0FB6OKiOjo50tz2i8hBFEZmZmXj48CEMDQ2l5zEUhwkCERERURVjYpL/8MCCJIGoIhgaGkqfrZIwQSAiIiKqYgRBgKmpKWrWrImcnJzKDoc+AOrq6qWOHBRggkBERERURamqqir9pY6oovBBaUREREREJGGCQEREREREEiYIREREREQkYYJAREREREQSJghERERERCRhgkBERERERBImCEREREREJGGCQEREREREEiYIREREREQkYYJAREREREQSJghERERERCRhgkBERERERBImCEREREREJGGCQEREREREEiYIREREREQkYYJAREREREQSJghERERERCRhgkBERERERBImCEREREREJGGCQEREREREEiYIREREREQkYYJAREREREQSJghERERERCRhgkBERERERBImCEREREREJGGCQEREREREEiYIREREREQkYYJAREREREQSJghERERERCRhgkBERERERBImCEREREREJGGCQEREREREEiYIREREREQkYYJAREREREQSJghERERERCRRq+wAiIiIiN6FJ1mZiE27j5e5OdBSU4edoQmMNHUqOyyiKocJAhEREX3QEp6l4HDSVVxOvQe5KEr7VQQBTtXM0MncAZZ61SsxQqKqhVOMKlBQUBAMDQ3fej+ZmZno2bMn9PX1IQgC0tLS3nqflSkhIQGCICAqKqpC27W0tMTKlStLLCMIAvbt21dkHCdOnPgorj8R0fss8nESvo8+hqiUfxWSAwCQiyKiUv7NP/44qZIiJKp6KjVB8PPzQ/fu3SszhHIr6stlnz59cOPGjbfe95YtW3Dq1CmcOXMGycnJMDAweOt9VoTyfqE2NzdHcnIyGjVq9HYCK0FycjI6depU5DF3d3eF6/+uEkQiIlJOwrMU/HQ9HLmivMRyuaIcP14PR8KzlHcUGVHVxhGECqStrY2aNWu+9X5u374NOzs7NGrUCCYmJhAEocxt5OXlQS4v+Q9mVaGqqgoTExOoqb37GXEmJibQ1NQs8piGhka5rz8REb19h5OulpocFMgV5QhJuvaWIyJ6P1SpBKF169YYN24cJk2ahGrVqsHExASzZ89WKCMIAn766Sf06NEDOjo6sLGxQXBwsEKZkydPws3NDZqamjA1NcWUKVOQm5sLANi0aRNq165d6Muxj48PBg8eDCD/C7iPjw9q1aoFmUyGZs2a4fjx4wpx3r17F9988w0EQZC+IBb1C/L69etRv359aGhowNbWFlu3bi3z+bx+jQICAvD3339DEAS0bt0aAPDkyRMMGDAARkZG0NHRQadOnXDz5k2pXkFswcHBsLe3h6amJhITEwu1/+TJE/j6+sLY2Bja2tqwsbFBYGAggKJHAKKioiAIAhISEgAAd+/ehbe3N4yMjKCrqwsHBwccOnQICQkJaNOmDQDAyMgIgiDAz88PABASEoJPP/0UhoaGqF69Orp27Yrbt29LfRQ3tSc0NBSurq7Q0dGBu7s74uLipDqlvYcFnj17hn79+kFXVxdmZmZYu3ZtofenYIrR6169HidOnMCgQYOQnp4ufSZmz56NuXPnFjny0bhxY8yYMaPIdomI6M09ycrE5ZR7ZaoTnfovnmRlvqWIiN4fVSpBAPKnz+jq6uLcuXNYunQp5s6di2PHjimUmTNnDnr37o3Lly+jc+fO8PX1RWpqKgDg3r176Ny5M5o1a4bo6GisX78eP//8M+bPnw8A6NWrF1JSUhAWFia1l5qaipCQEPj6+gIAMjIy0LlzZ4SGhiIyMhIdO3aEt7e39IV6z549qFOnDubOnYvk5GQkJycXeS579+7F+PHjMXHiRFy5cgXDhw/HoEGDFPou7Xxet2fPHgwbNgwtWrRAcnIy9uzZAyB/utaFCxcQHByMs2fPQhRFdO7cGTk5OVLdzMxMLFmyBD/99BOuXr1a5GjHjBkzcO3aNRw+fBixsbFYv349atSoUfwb9prRo0cjKysLf//9N2JiYrBkyRLIZDKYm5tj9+7dAIC4uDgkJyfjhx9+AAA8f/4c3377LS5cuIDQ0FCoqKigR48epY5wTJs2DQEBAbhw4QLU1NSkBA8o/T0s8P3338PZ2RmRkZGYMmUKxo8fX+jzpgx3d3esXLkS+vr60mfC398fgwcPRmxsLM6fPy+VjYyMxOXLlzFo0KBC7WRlZeHp06cKLyIiKrvYtPuQQyy94CvkoojrafffUkRE7xGxEg0cOFD08fGRtj09PcVPP/1UoUyzZs3EyZMnS9sAxOnTp0vbGRkZIgDx8OHDoiiK4v/93/+Jtra2olwul8qsXbtWlMlkYl5eniiKoujj4yMOHjxYOr5x40axdu3a0vGiODg4iKtXr5a269atK65YsUKhTGBgoGhgYCBtu7u7i8OGDVMo06tXL7Fz585Kn09Rxo8fL3p6ekrbN27cEAGI4eHh0r7Hjx+L2tra4u+//y7FBkCMiooqtl1RFEVvb29x0KBBRR4LCwsTAYhPnjyR9kVGRooAxDt37oiiKIqOjo7i7Nmzla5flEePHokAxJiYGFEURfHOnTsiADEyMlKhnePHj0t1Dh48KAIQX7x4UWy7Rb2HHTt2VCjTp08fsVOnTtI2AHHv3r0lxlFwPq+//wU6deokjhw5UtoeO3as2Lp16yJjnDVrlgig0Cs9Pb3Y8yIiosJC/70ufv33tjK/Qv+9XmK76enp/LtMH7wqN4Lg5OSksG1qaoqHDx8WW0ZXVxf6+vpSmdjYWLRo0UJhXriHhwcyMjLw77//AgB8fX2xe/duZGVlAQC2bduGvn37QkUl/3JkZGTA398fdnZ2MDQ0hEwmQ2xsbJFTckoSGxsLDw8PhX0eHh6IjY1V+nyU7UdNTQ3NmzeX9lWvXh22trYKfWloaBS6vq8bOXIkduzYgcaNG2PSpEk4c+aM0nEAwLhx4zB//nx4eHhg1qxZuHz5cql1bt68iX79+sHKygr6+vqwtLQEgFKv96vnYmpqCgDSdVP2PWzRokWh7dffnzc1bNgwbN++HS9fvkR2djZ+++03hdGOV02dOhXp6enSKymJd9UgIioPLTX1ctXTLmc9og9JlUsQ1NUV/2EKglBoqokyZUri7e0NURRx8OBBJCUl4dSpU9L0IgDw9/fH3r17sXDhQpw6dQpRUVFwdHREdnZ2Oc6odG96PsrS1tYudUFtp06dpPUV//33H9q1awd/f38AkBIo8ZXbxL06hQkAhg4divj4ePTv3x8xMTFwdXXF6tWrS+zT29sbqamp+PHHH3Hu3DmcO3cOAEq93q9et4LzKrhu7/o9LIm3tzc0NTWxd+9e/Pnnn8jJycEXX3xRZFlNTU3o6+srvIiIqOzsDE2gUsabSKgIAhoamryliIjeH1UuQXhTdnZ20hz8AuHh4dDT00OdOnUAAFpaWvj888+xbds2bN++Hba2tmjSpIlCeT8/P/To0QOOjo4wMTGRFuEW0NDQQF5eXqmxhIeHK+wLDw+Hvb39G55l4X5yc3OlL9YAkJKSgri4uHL1ZWxsjIEDB+LXX3/FypUrsWnTJmk/AIU1F0U9m8Dc3BwjRozAnj17MHHiRPz4448A8q8ZAIXrVhDn9OnT0a5dO9jZ2eHJkydljvl1yryHAPDPP/8U2razsytXn8V9JtTU1DBw4EAEBgYiMDAQffv2hba2drn6ICIi5Rhp6sCpmlmZ6jhXq8MnKxPhA3yS8qhRo7By5UqMHTsWY8aMQVxcHGbNmoVvv/1W+gUcyJ9m1LVrV1y9ehVfffWVQhs2NjbYs2cPvL29IQgCZsyYUegXfUtLS/z999/o27cvNDU1i1zI+91336F3795wcXFB+/bt8eeff2LPnj1F3k3nTdjY2MDHxwfDhg3Dxo0boaenhylTpsDMzAw+Pj5lamvmzJlo2rQpHBwckJWVhQMHDkhfmK2trWFubo7Zs2djwYIFuHHjBgICAhTqT5gwAZ06dUKDBg3w5MkThIWFSfXr1q0LQRBw4MABdO7cGdra2jAyMkL16tWxadMmmJqaIjExEVOmTKmQa1LaewjkJxJLly5F9+7dcezYMezatQsHDx4sV5+WlpbIyMhAaGgonJ2doaOjAx2d/P/RDB06VLoOryeNRET0dnQyd8CV1P+UutWpuooqOppX7A94RO+rD24EwczMDIcOHUJERAScnZ0xYsQIDBkyBNOnT1co17ZtW1SrVg1xcXH48ssvFY4tX74cRkZGcHd3h7e3N7y8vBRGGABg7ty5SEhIQP369aVf1l/XvXt3/PDDD1i2bBkcHBywceNGBAYGSrcmrUiBgYFo2rQpunbtihYtWkAURRw6dKjQ9KXSaGhoYOrUqXByckKrVq2gqqqKHTt2AMif0rN9+3Zcv34dTk5OWLJkiXR3qAJ5eXkYPXo07Ozs0LFjRzRo0ADr1q0DkP/ezJkzB1OmTEGtWrUwZswYqKioYMeOHbh48SIaNWqEb775Bt9///0bXw9l3kMAmDhxIi5cuAAXFxfMnz8fy5cvh5eXV7n6dHd3x4gRI9CnTx8YGxtj6dKl0jEbGxu4u7ujYcOGCmtFiIjo7bHUq45hDT2gJpT8dUdNUMFQW3dY6lV/R5ERVW2CKIpluwcYEZWZKIqwsbHBqFGj8O233ypd7+nTpzAwMEB6ejrXIxARlVPCsxSEJF1DdOq/kL/ytUdFEOBcrQ46mtsrnRzw7zJ9DD64KUZEVc2jR4+wY8cO3L9/v8hnHxAR0dtlqVcdI+xb4klWJq6n3ceL3Bxoq6mjoaEJ1xwQFYEJAtFbVrNmTdSoUQObNm2CkZFRZYdDRPTRMtLUQYtaVpUdBlGVxwSB6C3jLD4iIiJ6n3xwi5SJiIiIiKj8mCAQEREREZGECQIREREREUmYIBARERERkYQJAhERERERSZggEBERERGRhAkCERERERFJmCAQEREREZGECQIREREREUmYIBARERERkYQJAhERERERSZggEBERERGRhAkCERERERFJmCAQEREREZGECQIREREREUmYIBARERERkYQJAhERERERSZggEBERERGRhAkCERERERFJmCAQEREREZGECQIREREREUmYIBARERERkYQJAhERERERSZggEBERERGRhAkCERERERFJmCAQEREREZGECQIREREREUmYIBARERERkYQJAhERERERSZggEBERERGRhAkCERERERFJmCAQEREREZGECQIREREREUmYIBARERERkYQJAhERERERSZggEBERERGRhAkCERERERFJmCAQEREREZGECQIREREREUnUKjsAIiIiondBfPYEYuJVIOsloKkFwcIBgp5RZYdFVOUwQSAiIqIPmng/AfKIg0B8NCDP+99+FVXAyhkqbl0gmFhWXoBEVQwTBCIiIvpgiTcvQX5oI5CXW/igPA+4dQnyO5eh0mU4BOsm7z5AoiqIaxCIlODn5wdBECAIAtTV1VGrVi106NABmzdvhlwul8pZWlpK5V59LV68GACQkJAAQRAQFRVVSWdCRPTxEO8nFJ8cvCovF/KDGyHeT3gncRFVdUwQiJTUsWNHJCcnIyEhAYcPH0abNm0wfvx4dO3aFbm5//ufz9y5c5GcnKzwGjt2bCVGTkT0cZJHHCw9OSiQl5tfnog4xYhIWZqamjAxMQEAmJmZoUmTJvjkk0/Qrl07BAUFYejQoQAAPT09qRwREVUO8dkT4HZU2SrFR0N89oQLl+mjxxEEojfQtm1bODs7Y8+ePRXSXlZWFp4+farwIiKishMTrwKivPSCr5LnQUy89nYCInqPMEEgekMNGzZEQkKCtD158mTIZDKF16lTp5Rqa9GiRTAwMJBe5ubmbylqIqIPXNbL8tXLLmc9og8IpxgRvSFRFCEIgrT93Xffwc/PT6GMmZmZUm1NnToV3377rbT99OlTJglEROWhqVW+ehrlrEf0AWGCQPSGYmNjUa9ePWm7Ro0asLa2Lldbmpqa0NTUrKjQiIg+WoKFQ/5zDl557kGpVFQhWNi/vaCI3hOcYkT0Bv766y/ExMSgZ8+elR0KERG9QtAzAqycy1bJypkLlInAEQQipWVlZeH+/fvIy8vDgwcPEBISgkWLFqFr164YMGCAVO7Zs2e4f/++Ql0dHR3o6+u/65CJiD5qKm5dIL9zWblbnaqqQ8Wty9sPiug9wBEEIiWFhITA1NQUlpaW6NixI8LCwrBq1Srs378fqqqqUrmZM2fC1NRU4TVp0qRKjJyI6OMkmFhCpctwQLWU30NV1aDS5WsIJpbvJC6iqk4QRVGs7CCIqGhPnz6FgYEB0tPTOQJBRFRO4v2E/IegxUcrrklQUQWsnKHi1kXp5IB/l+ljwClGRERE9EETTCyh2m00xGdP8p9zkP0S0NCCYGHPNQdERWCCQERERB8FQc8IgoNHZYdBVOVxDQIREREREUmYIBARERERkYQJAhERERERSZggEBERERGRhAkCERERERFJmCAQEREREZGECQIREREREUmYIBARERERkYQJAhERERERSZggEBERERGRhAkCERERERFJmCAQEREREZGECQIREREREUmYIBARERERkYQJAhERERERSZggEBERERGRhAkCERERERFJmCAQEREREZGECQIREREREUmYIBARERERkYQJAhERERERSZggEBERERGRhAkCERERERFJmCAQEREREZGECQIREREREUmYIBARERERkYQJAhERERERSZggEBERERGRhAkCERERERFJmCAQEREREZGECQIREREREUmYIBARERERkYQJAhERERERSZggEBERERGRhAkCERERERFJ1Mpb8eXLl7h8+TIePnwIuVyucKxbt25vHBgREREREb175UoQQkJCMGDAADx+/LjQMUEQkJeX98aBERERERHRu1euKUZjx45Fr169kJycDLlcrvBickBERERE9P4qV4Lw4MEDfPvtt6hVq1ZFx0NERERERJWoXAnCF198gRMnTlRwKEREREREVNkEURTFslbKzMxEr169YGxsDEdHR6irqyscHzduXIUFSPQxe/r0KQwMDJCeng59ff3KDoeI6KPHv8v0MSjXIuXt27fj6NGj0NLSwokTJyAIgnRMEAQmCERVhPjsCcTEq0DWS0BTC4KFAwQ9o8oOi4iIiKqwciUI06ZNw5w5czBlyhSoqPBRClWFIAjYu3cvunfvXtmhUCUT7ydAHnEQiI8G5P+7cYCoogpYOUPFrQsEE8vKC5CIiIiqrHJ9u8/OzkafPn2qbHJw//59jB07FlZWVtDU1IS5uTm8vb0RGhpa2aG9VcnJyejUqRMAICEhAYIgICoqqnKDIsm7ek/Em5cg37kIuHVJITkAkL99K/+4eOvSW42DiIiI3k/l+oY/cOBA7Ny5s6JjqRAJCQlo2rQp/vrrL3z//feIiYlBSEgI2rRpg9GjR1d2eG+ViYkJNDU1KzsMqkTi/QTID20E8nJLLpiXC/nBjRDvJ7yTuIiIiOj9Ua4EIS8vD0uXLoWnpyfGjh2Lb7/9VuFVmUaNGgVBEBAREYGePXuiQYMGcHBwwLfffot//vlHKpeYmAgfHx/IZDLo6+ujd+/eePDggXR89uzZaNy4MTZv3gwLCwvIZDKMGjVKOncTExPUrFkTCxYsUOhfEARs3LgRXbt2hY6ODuzs7HD27FncunULrVu3hq6uLtzd3XH79m2pjp+fX6FpQRMmTEDr1q2l7datW2PcuHGYNGkSqlWrBhMTE8yePbtQ3/v27QMA1KtXDwDg4uICQRDQunVr/P3331BXV8f9+/cL9dWyZctir2laWhqGDh0KY2Nj6Ovro23btoiOji50rbZu3QpLS0sYGBigb9++ePbsmVTm2bNn8PX1ha6uLkxNTbFixQq0bt0aEyZMkMps3boVrq6u0NPTg4mJCb788ks8fPhQIZbg4GDY2NhAS0sLbdq0wZYtWyAIAtLS0qQyp0+fRsuWLaGtrQ1zc3OMGzcOz58/l45bWlpi/vz5GDBgAGQyGerWrYvg4GA8evRI+kw4OTnhwoULCn0r0+7ChQsxePBg6OnpwcLCAps2bZKOF/WeVDR5xMHSk4MCebn55YmIiIheUa4EISYmBi4uLlBRUcGVK1cQGRkpvSpzSktqaipCQkIwevRo6OrqFjpuaGgIAJDL5fDx8UFqaipOnjyJY8eOIT4+Hn369FEof/v2bRw+fBghISHYvn07fv75Z3Tp0gX//vsvTp48iSVLlmD69Ok4d+6cQr158+ZhwIABiIqKQsOGDfHll19i+PDhmDp1Ki5cuABRFDFmzJgyn9+WLVugq6uLc+fOYenSpZg7dy6OHTtWZNmIiAgAwPHjx5GcnIw9e/agVatWsLKywtatW6VyOTk52LZtGwYPHlxsv7169cLDhw9x+PBhXLx4EU2aNEG7du2QmpqqcK327duHAwcO4MCBAzh58iQWL14sHf/2228RHh6O4OBgHDt2DKdOncKlS4pTXHJycjBv3jxER0dj3759SEhIgJ+fn3T8zp07+OKLL9C9e3dER0dj+PDhmDZtmkIbt2/fRseOHdGzZ09cvnwZO3fuxOnTpwtd7xUrVsDDwwORkZHo0qUL+vfvjwEDBuCrr77CpUuXUL9+fQwYMAAFN/lStt2AgAC4uroiMjISo0aNwsiRIxEXF1fse1KRxGdPgNtRZasUH51fj4iIiKiA+AE5d+6cCEDcs2dPieWOHj0qqqqqiomJidK+q1evigDEiIgIURRFcdasWaKOjo749OlTqYyXl5doaWkp5uXlSftsbW3FRYsWSdsAxOnTp0vbZ8+eFQGIP//8s7Rv+/btopaWlrQ9cOBA0cfHRyHG8ePHi56entK2p6en+OmnnyqUadasmTh58mSFvvfu3SuKoijeuXNHBCBGRkYq1FmyZIloZ2cnbe/evVuUyWRiRkZGoeskiqJ46tQpUV9fX3z58qXC/vr164sbN24URbHoa/Xdd9+JzZs3F0VRFJ8+fSqqq6uLu3btko6npaWJOjo64vjx44vsVxRF8fz58yIA8dmzZ6IoiuLkyZPFRo0aKZSZNm2aCEB88uSJKIqiOGTIEPHrr78udA4qKiriixcvRFEUxbp164pfffWVdDw5OVkEIM6YMUPaV/C+JScnl7tduVwu1qxZU1y/fr0oisW/J696+fKlmJ6eLr2SkpJEAGJ6enqxdQrkXTkl5gYMLvMr78rpUtsmIqJ86enpSv9dJnpfvdEq41u3buHIkSN48eJFQbLxJs29MWX7j42Nhbm5OczNzaV99vb2MDQ0RGxsrLTP0tISenp60natWrVgb2+vsDi7Vq1ahabBODk5KRwHAEdHR4V9L1++xNOnT5U8s8LtAoCpqWmhvkvj5+eHW7duSdOtgoKC0Lt37yJHXAAgOjoaGRkZqF69OmQymfS6c+eOwjSp16/Vq7HFx8cjJycHbm5u0nEDAwPY2toq9HXx4kV4e3vDwsICenp68PT0BJA/HQwA4uLi0KxZM4U6r7ZZEG9QUJBCrF5eXpDL5bhz545UTpn3CIB0DuVpVxAEmJiYlOk9WrRoEQwMDKTXq5/RUmW9VL7sq7LLWY+IiIg+SOW6zWlKSgp69+6NsLAwCIKAmzdvwsrKCkOGDIGRkRECAgIqOk6l2NjYQBAEXL9+vULae/0BcIIgFLlPLpcXW6/gGRFF7Suop6KiUii5ycnJUSqe1/suTc2aNeHt7Y3AwEDUq1cPhw8fLvGp2BkZGTA1NS2yTMGUrYqI7fnz5/Dy8oKXlxe2bdsGY2NjJCYmwsvLC9nZ2Uq3k5GRgeHDhxf5LA4LC4si41XmPSpPuwXtlOU6TJ06VWEdz9OnT5VPEjS1lO5HgUY56xEREdEHqVwJwjfffAN1dXUkJibCzs5O2t+nTx98++23lZYgVKtWDV5eXli7di3GjRtX6FfxtLQ0GBoaws7ODklJSUhKSpK+fF27dg1paWmwt7d/53EbGxvjypUrCvuioqIKfdksCw0NDQD5C8pfN3ToUPTr1w916tRB/fr14eHhUWw7TZo0wf3796GmpgZLS8tyxWJlZQV1dXWcP39e+jKdnp6OGzduoFWrVgCA69evIyUlBYsXL5bek9cXCdva2uLQoUMK+86fP18o3mvXrsHa2rpcsRanItot6T0poKmpWe47UQkWDvnPOXj91qYlUVGFYPHuP/NERERUdZVritHRo0exZMkS1KlTR2G/jY0N7t69WyGBldfatWuRl5cHNzc37N69Gzdv3kRsbCxWrVqFFi1aAADat28PR0dH+Pr64tKlS4iIiMCAAQPg6ekJV1fXdx5z27ZtceHCBfzyyy+4efMmZs2aVShhKKuaNWtCW1sbISEhePDgAdLT06VjXl5e0NfXx/z58zFo0KAS22nfvj1atGiB7t274+jRo0hISMCZM2cwbdq0Ql/gi6Onp4eBAwfiu+++Q1hYGK5evYohQ4ZARUVF+qXewsICGhoaWL16NeLj4xEcHIx58+YptDN8+HBcv34dkydPxo0bN/D7778jKCgIwP9+8Z88eTLOnDmDMWPGICoqCjdv3sT+/fvLtSj8VRXRbknvSUUQ9IwAK+eyVbJy5pOViYiISEG5EoTnz59DR0en0P7U1NRKvw+/lZUVLl26hDZt2mDixIlo1KgROnTogNDQUKxfvx5A/pfJ/fv3w8jICK1atUL79u1hZWVVac928PLywowZMzBp0iQ0a9YMz549w4ABA96oTTU1NaxatQobN25E7dq14ePjIx1TUVGBn58f8vLySu1HEAQcOnQIrVq1wqBBg9CgQQP07dsXd+/elebpK2P58uVo0aIFunbtivbt28PDwwN2dnbQ0sqf3mJsbIygoCDs2rUL9vb2WLx4MZYtW6bQRr169fDHH39gz549cHJywvr166W7GBV87pycnHDy5EncuHEDLVu2hIuLC2bOnInatWsrHWtRKqLdkt6TiqLi1gVQVXJgUFU9vzwRERHRKwSxHCuLO3fujKZNm2LevHnQ09PD5cuXUbduXfTt2xdyuRx//PHH24iVKtCQIUPw6NEjBAcHV0r/z58/h5mZGQICAjBkyJByt7NgwQJs2LABSUlJFRhd1fH06VMYGBggPT0d+vr6StURb12C/GApD0tTVYNKl+EQrJtUUKRERB+H8vxdJnrflGsNwtKlS9GuXTtcuHAB2dnZmDRpEq5evYrU1FSEh4dXdIxUgdLT0xETE4PffvvtnSYHkZGRuH79Otzc3JCeno65c+cCQJl/RV+3bh2aNWuG6tWrIzw8HN9///0bTx/60AjWTaDSZ2r+Q9DioxXXJKioAlbOUHHrAsHEstJiJCIioqqrXAlCo0aNcOPGDaxZswZ6enrIyMjA559/jtGjR8PU1LSiY6QK5OPjg4iICIwYMQIdOnR4p30vW7YMcXFx0NDQQNOmTXHq1CnUqFGjTG3cvHkT8+fPR2pqKiwsLDBx4kRMnTr1LUX8/hJMLKHabTTEZ08gJl7Lv5WphhYEC3uuOSAiIqISlWuKUWJiIszNzaWFoa8fe/W2j0RUfhzKJiKqWvh3mT4G5VqkXK9ePTx69KjQ/pSUFNSrV++NgyIiIiIiospRrgRBFMUiRw8yMjKku9IQEREREdH7p0xrEAqe8CoIAmbMmKFwq9O8vDycO3cOjRs3rtAAiYiIiIjo3SlTghAZGQkgfwQhJiZGejIskP+UWGdnZ/j7+1dshERERERE9M6UKUEICwsDAAwaNAirVq2Cnp7eWwmKiIiIiIgqR5kShM8//1z674EDBxZbbs+ePeWPiIiIiIiIKk2ZEgQDA4O3FQcREREREVUBZUoQAgMD31YcRERERERUBZTrNqdERERERPRhYoJAREREREQSJghERERERCRhgkBERERERBImCEREREREJGGCQEREREREEiYIREREREQkYYJAREREREQSJghERERERCRhgkBERERERBImCEREREREJGGCQEREREREEiYIREREREQkYYJAREREREQSJghERERERCRhgkBERERERBImCEREREREJGGCQEREREREEiYIREREREQkYYJAREREREQSJghERERERCRhgkBERERERBImCEREREREJGGCQEREREREEiYIREREREQkYYJAREREREQSJghERERERCRhgkBERERERBImCEREREREJGGCQEREREREEiYIREREREQkYYJAREREREQStcoOgIjeHvHZE4iJV4Gsl4CmFgQLBwh6RpUdFhEREVVhHEEohaWlJVauXFnu+q1bt8aECRPeKIbZs2ejcePGJZbx8/ND9+7d36ifqiIoKAiGhoZKl3/T96gsBEHAvn373klfb0K8n4C84LWQ/zwZ4pFAiCe2QzwSCPnPk5EXvBbi/YTKDpGIiIiqqA8iQXj06BFGjhwJCwsLaGpqwsTEBF5eXggPD5fKvC9f7D42RX2579OnD27cuKF0G+fPn8fXX39doXEVl5QlJyejU6dOFdpXRRNvXoJ85yLg1iVAnqd4UJ4H3Mo/Lt66VDkBEhERUZX2QUwx6tmzJ7Kzs7FlyxZYWVnhwYMHCA0NRUpKSmWH9t4QRRF5eXlQU3s3H4ns7GxoaGgUeUxbWxva2tpKt2VsbFxRYZXKxMTknfVVHuL9BMgPbQTycksumJcL+cGNUOkzFYKJ5TuJjYiIiN4P7/0IQlpaGk6dOoUlS5agTZs2qFu3Ltzc3DB16lR069YNQP6v1ADQo0cPCIIgbd++fRs+Pj6oVasWZDIZmjVrhuPHj5fY308//QRDQ0OEhoYCAK5cuYJOnTpBJpOhVq1a6N+/Px4/fqxQRy6XY9KkSahWrRpMTEwwe/ZsheOJiYnw8fGBTCaDvr4+evfujQcPHhQbQ15eHr799lsYGhqievXqmDRpEkRRLNTnokWLUK9ePWhra8PZ2Rl//PGHdPzEiRMQBAGHDx9G06ZNoampidOnTxfqKyEhAYIgYMeOHXB3d4eWlhYaNWqEkydPKsQzZMgQqS9bW1v88MMPCu0UTIFasGABateuDVtbW7Ru3Rp3797FN998A0EQIAgCgKKnGP35559o1qwZtLS0UKNGDfTo0UM69voohCAIWL9+PTp16gRtbW1YWVkpnDsATJ48GQ0aNICOjg6srKwwY8YM5OTkSP3PmTMH0dHRUlxBQUFS26+ORMXExKBt27bQ1tZG9erV8fXXXyMjI6PQeS9btgympqaoXr06Ro8eLfVV0eQRB0tPDgrk5eaXJyIiInrFe58gyGQyyGQy7Nu3D1lZWUWWOX/+PAAgMDAQycnJ0nZGRgY6d+6M0NBQREZGomPHjvD29kZiYmKR7SxduhRTpkzB0aNH0a5dO6SlpaFt27ZwcXHBhQsXEBISggcPHqB3794K9bZs2QJdXV2cO3cOS5cuxdy5c3Hs2DEA+V/kfXx8kJqaipMnT+LYsWOIj49Hnz59ij3ngIAABAUFYfPmzTh9+jRSU1Oxd+9ehTKLFi3CL7/8gg0bNuDq1av45ptv8NVXXyl8sQeAKVOmYPHixYiNjYWTk1OxfX733XeYOHEiIiMj0aJFC3h7e0sjNHK5HHXq1MGuXbtw7do1zJw5E//3f/+H33//XaGN0NBQxMXF4dixYzhw4AD27NmDOnXqYO7cuUhOTkZycnKRfR88eBA9evRA586dERkZidDQULi5uRUbKwDMmDEDPXv2RHR0NHx9fdG3b1/ExsZKx/X09BAUFIRr167hhx9+wI8//ogVK1YAyJ/iNHHiRDg4OEhxFfV+PH/+HF5eXjAyMsL58+exa9cuHD9+HGPGjFEoFxYWhtu3byMsLAxbtmxBUFCQlHBUJPHZE+B2VNkqxUfn1yMiIiIqIH4A/vjjD9HIyEjU0tIS3d3dxalTp4rR0dEKZQCIe/fuLbUtBwcHcfXq1dJ23bp1xRUrVoiTJk0STU1NxStXrkjH5s2bJ3722WcK9ZOSkkQAYlxcnCiKoujp6Sl++umnCmWaNWsmTp48WRRFUTx69KioqqoqJiYmSsevXr0qAhAjIiJEURTFWbNmic7OztJxU1NTcenSpdJ2Tk6OWKdOHdHHx0cURVF8+fKlqKOjI545c0ah3yFDhoj9+vUTRVEUw8LCRADivn37Srwed+7cEQGIixcvLtTfkiVLiq03evRosWfPntL2wIEDxVq1aolZWVkK5Qqu76sCAwNFAwMDabtFixair69vsX293gYAccSIEQplmjdvLo4cObLYNr7//nuxadOm0vbr1/zVtgs+R5s2bRKNjIzEjIwM6fjBgwdFFRUV8f79+6Io5p933bp1xdzcXKlMr169xD59+hQZx8uXL8X09HTpVfB5Sk9PLzb2AnlXTom5AYPL/Mq7crrUtomIKF96errSf5eJ3lfv/QgCkL8G4b///kNwcDA6duyIEydOoEmTJqX+SpuRkQF/f3/Y2dnB0NAQMpkMsbGxhUYQAgIC8OOPP+L06dNwcHCQ9kdHRyMsLEwaxZDJZGjYsCGA/OlLBV7/Zd7U1BQPHz4EAMTGxsLc3Bzm5ubScXt7exgaGir84l0gPT0dycnJaN68ubRPTU0Nrq6u0vatW7eQmZmJDh06KMT2yy+/KMQFQKFeSVq0aFGov1fjW7t2LZo2bQpjY2PIZDJs2rSp0HV0dHQsdt1BSaKiotCuXbsy1Xk13oLtV+PduXMnPDw8YGJiAplMhunTpxc7clSc2NhYODs7Q1dXV9rn4eEBuVyOuLg4aZ+DgwNUVVWl7Vff/9ctWrQIBgYG0uvVz0Wpsl6WKX5JdjnrERER0Qfpg0gQAEBLSwsdOnTAjBkzcObMGfj5+WHWrFkl1vH398fevXuxcOFCnDp1ClFRUXB0dER2drZCuZYtWyIvL6/QlJmMjAx4e3sjKipK4XXz5k20atVKKqeurq5QTxAEyOXyNzzj4hXMgT948KBCXNeuXSs0F//VL7fltWPHDvj7+2PIkCE4evQooqKiMGjQoELXsbx9lWXBsjLOnj0LX19fdO7cGQcOHEBkZCSmTZtWKN6KUpb3f+rUqUhPT5deSUlJynekqVW+ADXKWY+IiIg+SB9MgvA6e3t7PH/+XNpWV1dHXp7iLR/Dw8Ph5+eHHj16wNHRESYmJkhISCjUlpubGw4fPoyFCxdi2bJl0v4mTZrg6tWrsLS0hLW1tcJL2S/DdnZ2SEpKUvgieO3aNaSlpcHe3r5QeQMDA5iamuLcuXPSvtzcXFy8eFHh3DU1NZGYmFgorjL9Iv2Kf/75p1B/dnZ2APKvo7u7O0aNGgUXFxdYW1sXGqkojoaGRqH35XVOTk7SovDyxFuwXRDvmTNnULduXUybNg2urq6wsbHB3bt3yxyXnZ0doqOjFT5n4eHhUFFRga2tbZniLaCpqQl9fX2Fl7IECwdARbX0gq9SUYVgUfhzRkRERB+v9z5BSElJQdu2bfHrr7/i8uXLuHPnDnbt2oWlS5fCx8dHKmdpaYnQ0FDcv38fT57kL8q0sbHBnj17EBUVhejoaHz55ZfF/rLr7u6OQ4cOYc6cOdIdc0aPHo3U1FT069cP58+fx+3bt3HkyBEMGjSo1C+XBdq3bw9HR0f4+vri0qVLiIiIwIABA+Dp6Vns9J/x48dj8eLF2LdvH65fv45Ro0YhLS1NOq6npwd/f39888032LJlC27fvo1Lly5h9erV2LJli1JxvW7t2rXYu3cvrl+/jtGjR+PJkycYPHgwgPzreOHCBRw5cgQ3btzAjBkzpIXgpbG0tMTff/+Ne/fuFbr7U4FZs2Zh+/btmDVrFmJjYxETE4MlS5aU2O6uXbuwefNm3LhxA7NmzUJERIS0eNjGxgaJiYnYsWMHbt++jVWrVhVa5G1paYk7d+4gKioKjx8/LnIBvK+vL7S0tDBw4EBcuXIFYWFhGDt2LPr3749atWopdf4VSdAzAqycy1bJyplPViYiIiIF732CIJPJ0Lx5c6xYsQKtWrVCo0aNMGPGDAwbNgxr1qyRygUEBODYsWMwNzeHi4sLAGD58uUwMjKCu7s7vL294eXlhSZNmhTb16effoqDBw9i+vTpWL16NWrXro3w8HDk5eXhs88+g6OjIyZMmABDQ0OoqCh3aQVBwP79+2FkZIRWrVqhffv2sLKyws6dO4utM3HiRPTv3x8DBw5EixYtoKenp3DbTwCYN28eZsyYgUWLFsHOzg4dO3bEwYMHUa9ePaXiet3ixYuxePFiODs74/Tp0wgODkaNGjUAAMOHD8fnn3+OPn36oHnz5khJScGoUaOUanfu3LlISEhA/fr1i32eQevWrbFr1y4EBwejcePGaNu2LSIiIkpsd86cOdixYwecnJzwyy+/YPv27dKITLdu3fDNN99gzJgxaNy4Mc6cOYMZM2Yo1O/Zsyc6duyINm3awNjYGNu3by/Uh46ODo4cOYLU1FQ0a9YMX3zxBdq1a6fwuXvXVNy6AKpKPstCVT2/PBEREdErBFF87Qb6RK9ISEhAvXr1EBkZWeSThasiQRCwd+9edO/evbJDeWNPnz6FgYEB0tPTlZ5uJN66BPnBUh6WpqoGlS7DIVgXnxATEVFh5fm7TPS+ee9HEIhIkWDdBCp9pgLWTQqvSVBRBf7/cSYHREREVBQl5yIQ0ftEMLGEarfREJ89gZh4Lf9WphpaECzsueaAiIiISsQEgUpkaWmJ920W2vsW79sk6BlBcPCo7DCIiIjoPcIpRkREREREJGGCQEREREREEiYIREREREQkYYJAREREREQSJghERERERCRhgkBERERERBImCEREREREJGGCQEREREREEiYIREREREQkYYJAREREREQSJghERERERCRhgkBERERERBImCEREREREJGGCQEREREREEiYIREREREQkYYJAREREREQSJghERERERCRhgkBERERERBImCEREREREJGGCQEREREREEiYIREREREQkYYJAREREREQSJghERERERCRhgkBERERERBImCEREREREJGGCQEREREREEiYIREREREQkYYJAREREREQSJghERERERCRhgkBERERERBImCEREREREJGGCQEREREREEiYIREREREQkYYJAREREREQSJghERERERCRhgkBERERERBImCEREREREJGGCQEREREREEiYIREREREQkYYJAREREREQStcoOgIiIPmzPnmcjMfkpsnLyoKmuCgtTfejpalR2WEREVAwmCO+hhIQE1KtXD5GRkWjcuHGFlSUiqkj3Hz9HREwy4pPSIRdFab+KIMDK3ABujqYwqaFbiRESEVFROMWoivHz84MgCBAEAerq6qhXrx4mTZqEly9fSmXMzc2RnJyMRo0avbUYunfv/lbaJqKPw827T7Dz8HXcSkxTSA4AQC6KuJWY9v+PP6mkCImIqDhMEKqgjh07Ijk5GfHx8VixYgU2btyIWbNmScdVVVVhYmICNbXKHQDKycmp1P7fRF5eHuRyeWWHQfRBuv/4OQ79HY88uVhiuTy5iIMn43H/8fN3FBkRESmDCUIVpKmpCRMTE5ibm6N79+5o3749jh07Jh1PSEiAIAiIiooCADx58gS+vr4wNjaGtrY2bGxsEBgYWGTbeXl5GDx4MBo2bIjExMRCx2fPno0tW7Zg//790kjGiRMnpD537twJT09PaGlpYdu2bUhJSUG/fv1gZmYGHR0dODo6Yvv27Qpttm7dGuPGjcOkSZNQrVo1mJiYYPbs2dJxURQxe/ZsWFhYQFNTE7Vr18a4ceOk45aWlpg3bx769esHXV1dmJmZYe3atQp9LF++HI6OjtDV1YW5uTlGjRqFjIwM6XhQUBAMDQ0RHBwMe3t7aGpqIjExEVlZWfD394eZmRl0dXXRvHlznDhxolC9I0eOwM7ODjKZTErgXrV582Y4ODhAU1MTpqamGDNmDABg8ODB6Nq1q0LZnJwc1KxZEz///HOR7xHR+y4iJrnU5KBAnlxERExy6QWJiOidYYJQxV25cgVnzpyBhkbxC/pmzJiBa9eu4fDhw4iNjcX69etRo0aNQuWysrLQq1cvREVF4dSpU7CwsChUxt/fH71795a+BCcnJ8Pd3V06PmXKFIwfPx6xsbHw8vLCy5cv0bRpUxw8eBBXrlzB119/jf79+yMiIkKh3S1btkBXVxfnzp3D0qVLMXfuXCnp2b17tzRScvPmTezbtw+Ojo4K9b///ns4OzsjMjJSiuHVpElFRQWrVq3C1atXsWXLFvz111+YNGmSQhuZmZlYsmQJfvrpJ1y9ehU1a9bEmDFjcPbsWezYsQOXL19Gr1690LFjR9y8eVOh3rJly7B161b8/fffSExMhL+/v3R8/fr1GD16NL7++mvExMQgODgY1tbWAIChQ4ciJCREIaE4cOAAMjMz0adPn2LfU6L31bPn2bidlFamOvFJ6Xj2PPvtBERERGXGRcpV0IEDByCTyZCbm4usrCyoqKhgzZo1xZZPTEyEi4sLXF1dAeT/4v66jIwMdOnSBVlZWQgLC4OBgUGRbclkMmhrayMrKwsmJiaFjk+YMAGff/65wr5XvyyPHTsWR44cwe+//w43Nzdpv5OTkzRNysbGBmvWrEFoaCg6dOiAxMREmJiYoH379lBXV4eFhYVCXQDw8PDAlClTAAANGjRAeHg4VqxYgQ4dOkhxFbC0tMT8+fMxYsQIrFu3Ttqfk5ODdevWwdnZWbpugYGBSExMRO3ataVzCQkJQWBgIBYuXCjV27BhA+rXrw8AGDNmDObOnSu1O3/+fEycOBHjx4+X9jVr1gwA4O7uDltbW2zdulVKWAIDA9GrVy/IZLJC1zcrKwtZWVnS9tOnTwuVIarKEpOfQlRu8EAiF0UkJj+Fg3XhHzaIiOjd4whCFdSmTRtERUXh3LlzGDhwIAYNGoSePXsWW37kyJHYsWMHGjdujEmTJuHMmTOFyvTr1w/Pnz/H0aNHi00OlFGQhBTIy8vDvHnz4OjoiGrVqkEmk+HIkSOFpi85OTkpbJuamuLhw4cAgF69euHFixewsrLCsGHDsHfvXuTm5iqUb9GiRaHt2NhYafv48eNo164dzMzMoKenh/79+yMlJQWZmZlSGQ0NDYU4YmJikJeXhwYNGkAmk0mvkydP4vbt21I5HR0dKTl4PfaHDx/iv//+Q7t27Yq9ZkOHDpWmfD148ACHDx/G4MGDiyy7aNEiGBgYSC9zc/Ni2yWqirJy8spVL7uc9YiIqOIxQaiCdHV1YW1tDWdnZ2zevBnnzp0rcb56p06dcPfuXXzzzTfSl9VXf9UHgM6dO+Py5cs4e/bsG8f2qu+//x4//PADJk+ejLCwMERFRcHLywvZ2YrTBdTV1RW2BUGQFgmbm5sjLi4O69atg7a2NkaNGoVWrVopvQg6ISEBXbt2hZOTE3bv3o2LFy9KaxRejUNbWxuCIEjbGRkZUFVVxcWLFxEVFSW9YmNj8cMPP5QYu/j/fyLV1tYuNb4BAwYgPj4eZ8+exa+//op69eqhZcuWRZadOnUq0tPTpVdSUpJS14CoqtBUVy1XPY1y1iMioorHBKGKU1FRwf/93/9h+vTpePHiRbHljI2NMXDgQPz6669YuXIlNm3apHB85MiRWLx4Mbp164aTJ0+W2KeGhgby8pT7NS88PBw+Pj746quv4OzsDCsrK9y4cUOpuq/S1taGt7c3Vq1ahRMnTuDs2bOIiYmRjv/zzz8K5f/55x/Y2dkBAC5evAi5XI6AgAB88sknaNCgAf77779S+3RxcUFeXh4ePnwIa2trhVdR06uKoqenB0tLS4SGhhZbpnr16ujevTsCAwMRFBSEQYMGFVtWU1MT+vr6Ci+i94mFqT5UXknElaEiCLAw5WediKiqYILwHujVqxdUVVUL3bmnwMyZM7F//37cunULV69exYEDB6Qvz68aO3Ys5s+fj65du+L06dPF9mdpaYnLly8jLi4Ojx8/LvGXfBsbGxw7dgxnzpxBbGwshg8fjgcPHpTp/IKCgvDzzz/jypUriI+Px6+//gptbW3UrVtXKhMeHo6lS5fixo0bWLt2LXbt2iXN+be2tkZOTg5Wr16N+Ph4bN26FRs2bCi13wYNGsDX1xcDBgzAnj17cOfOHURERGDRokU4ePCg0vHPnj0bAQEBWLVqFW7evIlLly5h9erVCmWGDh2KLVu2IDY2FgMHDlS6baL3jZ6uBqzMyzaN0crcgE9WJiKqQpggvAfU1NQwZswYLF26FM+fF75fuIaGBqZOnQonJye0atUKqqqq2LFjR5FtTZgwAXPmzEHnzp2LXKsAAMOGDYOtrS1cXV1hbGyM8PDwYmObPn06mjRpAi8vL7Ru3RomJiZlfsiaoaEhfvzxR3h4eMDJyQnHjx/Hn3/+ierVq0tlJk6ciAsXLsDFxQXz58/H8uXL4eXlBQBwdnbG8uXLsWTJEjRq1Ajbtm3DokWLlOo7MDAQAwYMwMSJE2Fra4vu3bvj/PnzRd7hqTgDBw7EypUrsW7dOjg4OKBr164Kd0ECgPbt28PU1BReXl7SgmiiD5WboylUVZQbRVBVFeDmaPqWIyIiorIQRLGs95sgercsLS0xYcIEhTsVvW8yMjJgZmaGwMDAQneBKsnTp09hYGCA9PR0Tjei98qtxCc4eLLkh6Wpqgjo4mkFawujdxgZ0Zvh32X6GPA2p0RvkVwux+PHjxEQEABDQ0N069atskMieiesLYzQp1NDRMQkIz4pHfJXfotSEQRYmRvAzdEUJjV0S2iFiIgqAxMEorcoMTER9erVQ506dRAUFAQ1Nf6To4+HSQ1ddGtjjWfPs5GY/BTZOXnQUFeFhak+1xwQEVVh/LZCVV5CQkJlh1BulpaW4Cw++tjp6WrwIWhERO8RLlImIiIiIiIJEwQiIiIiIpIwQSAiIiIiIgkTBCIiIiIikjBBICIiIiIiCRMEIiIiIiKSMEEgIiIiIiIJEwQiIiIiIpIwQSAiIiIiIgkTBCIiIiIikjBBICIiIiIiCRMEIiIiIiKSMEEgIiIiIiIJEwQiIiIiIpIwQSAiIiIiIgkTBCIiIiIikjBBICIiIiIiCRMEIiIiIiKSMEEgIiIiIiIJEwQiIiIiIpIwQSAiIiIiIgkTBCIiIiIikjBBICIiIiIiCRMEIiIiIiKSMEEgIiIiIiIJEwQiIiIiIpIwQSAiIiIiIgkTBCIiIiIikjBBICIiIiIiCRMEIiIiIiKSMEEgIiIiIiIJEwQiIiIiIpIwQSAiIiIiIgkTBCIiIiIikjBBICIiIiIiCRMEIiIiIiKSMEEgIiIiIiIJEwQiIiIiIpIwQSAiIiIiIgkTBCIiIiIikqhVdgBE9PY8e56NxOSnyMrJg6a6KixM9aGnq1HZYREREVEVxgSB6AN0//FzRMQkIz4pHXJRlParCAKszA3g5mgKkxq6lRghERERVVWcYlQG9+/fx/jx42FtbQ0tLS3UqlULHh4eWL9+PTIzMys7vA/W7Nmz0bhx43fWn6WlJVauXPnO+qtoN+8+wc7D13ErMU0hOQAAuSjiVmLa/z/+pJIiJCIioqqMIwhKio+Ph4eHBwwNDbFw4UI4OjpCU1MTMTEx2LRpE8zMzNCtW7dKiy87OxsaGh/31JGcnByoq6tXdhiSynhP7j9+jkN/xyNPLpZYLk8u4uDJePTp1JAjCURERKSAIwhKGjVqFNTU1HDhwgX07t0bdnZ2sLKygo+PDw4ePAhvb2+pbGJiInx8fCCTyaCvr4/evXvjwYMHAIAbN25AEARcv35dof0VK1agfv360vaVK1fQqVMnyGQy1KpVC/3798fjx4+l461bt8aYMWMwYcIE1KhRA15eXjhx4gQEQUBoaChcXV2ho6MDd3d3xMXFSfVu374NHx8f1KpVCzKZDM2aNcPx48cVYrG0tMTChQsxePBg6OnpwcLCAps2bVIo8++//6Jfv36oVq0adHV14erqinPnzknH9+/fjyZNmkBLSwtWVlaYM2cOcnNzi72+J06cgJubG3R1dWFoaAgPDw/cvXsXQUFBmDNnDqKjoyEIAgRBQFBQEABAEASsX78e3bp1g66uLhYsWICgoCAYGhoqtL1v3z4IgqCw788//0SzZs2gpaWFGjVqoEePHtJ1vXv3Lr755hupP6DoUYyVK1fC0tJS2vbz80P37t2xYMEC1K5dG7a2tgCApKQk9O7dG4aGhqhWrRp8fHyQkJBQ7LV4ExExyaUmBwXy5CIiYpLfShxERET0/mKCoISUlBQcPXoUo0ePhq5u0b+2FnyRlMvl8PHxQWpqKk6ePIljx44hPj4effr0AQA0aNAArq6u2LZtm0L9bdu24csvvwQApKWloW3btnBxccGFCxcQEhKCBw8eoHfv3gp1tmzZAg0NDYSHh2PDhg3S/mnTpiEgIAAXLlyAmpoaBg8eLB3LyMhA586dERoaisjISHTs2BHe3t5ITExUaDsgIACurq6IjIzEqFGjMHLkSCnRyMjIgKenJ+7du4fg4GBER0dj0qRJkMvlAIBTp05hwIABGD9+PK5du4aNGzciKCgICxYsKPLa5ebmonv37vD09MTly5dx9uxZfP311xAEAX369MHEiRPh4OCA5ORkJCcnS9cSyP/i3qNHD8TExCicZ0kOHjyIHj16oHPnzoiMjERoaCjc3NwAAHv27EGdOnUwd+5cqb+yCA0NRVxcHI79v/buPayqKnHj+HtAQOVwU0kwQTJEEIEADbELYhqYUSaNSkymqVlqZsqUmqZGFysvj2U2laU1jnkZL+M4ppLlJbLEyzFS8oIXdAQ1U7n8Eg3O7w/HPR0BATUV/H6eZz9PZ++11l57uR8671lrn5OWpuXLl+vcuXOKi4uTi4uLNmzYoPT0dJnNZsXHx+vs2bPVarsyBUVnlX3oVLXq7Dt0WgVFV7cfAACgZmOJURXs3btXVqvV+ET4gkaNGunMmTOSpMGDB+vNN9/UmjVrlJmZqf3798vHx0eS9Nlnnyk4OFgZGRlq27atkpOTNX36dKWmpko6P6uwZcsWzZkzR5I0ffp0hYeH6/XXXzfO9cknn8jHx0e7d+9WQECAJKlFixZ66623jDIX3sy+9tpriomJkSSNHDlSXbt21ZkzZ1S3bl2FhYUpLCzMqJOamqolS5Zo2bJlGjJkiLH/gQce0KBBgyRJL774oqZOnaqvv/5aLVu21Ny5c3X8+HFlZGSoQYMGkiR/f3+j7oQJEzRy5Eg98cQTkqTmzZsrNTVVL7zwgsaNG1dmfPPz83X69Gk9+OCDxixKUFCQcdxsNqtOnTry8vIqU/exxx5T3759y+y/lNdee029evXShAkTjH0XxqRBgwayt7eXi4tLueerjLOzs2bOnGksLZozZ45KS0s1c+ZMI0TOmjVL7u7uWrt2re6//36b+sXFxSouLjZe5+fnV/ncObn5slZt8sBQarUqJzdfwf6NqlcRAADUWswgXIFNmzbJYrEoODjYeFOXlZUlHx8fIxxIUqtWreTu7q6srCxJUq9evXTgwAF99913ks7PHkRERCgwMFCStH37dn399dcym83GduFYdna20W5kZGS5/QoNDTX+29vbW5J07NgxSec//U9JSVFQUJDc3d1lNpuVlZVVZgbh922YTCZ5eXkZbVgsFoWHhxvh4GLbt2/XK6+8YtP/AQMGKDc3t9yHuRs0aKA+ffooLi5OCQkJmjZtWpU/uW/Tpk2Vyv2exWLRfffdV+16VRESEmLz3MH27du1d+9eubi4GGPRoEEDnTlzxubf8oI33nhDbm5uxvb7+6gyxedKLqvPZy+zHgAAqJ2YQagCf39/mUwmm7X80vlPxiWpXr161WrPy8tLHTt21Ny5c9WuXTvNnTtXzzzzjHG8sLBQCQkJevPNN8vUvfCGX1KFy51+/6Du75c+SVJKSorS0tI0adIk+fv7q169enr00UfLLHe5+GFfk8lktFHZ9RYWFmrChAnq3r17mWN169Ytt86sWbM0dOhQrVy5UvPnz9eYMWOUlpamdu3aXfJcF4+BnZ2drBd9jH7u3Dmb19X996pqu+X1p7CwUJGRkWWWlEmSp6dnmX2jRo3S8OHDjdf5+flVDglODvZVKncxx8usBwAAaicCQhU0bNhQnTt31vTp0/Xss89W+MZcOr805tChQzp06JDxxm7nzp06deqUWrVqZZRLTk7WCy+8oKSkJO3bt0+9evUyjkVERGjRokXy8/NTnTpX958oPT1dffr0MR7KLSwsrPYDs6GhoZo5c6Z++eWXcmcRIiIitGvXLptlR1URHh6u8PBwjRo1StHR0UaAcnR0VElJ1T7l9vT0VEFBgYqKiox/J4vFUqb/a9asqXBpUnnn8/T0VF5enqxWqxG6Lm63PBEREZo/f75uueUWubq6VlreyclJTk5OlZYrj6+3q+xMpjJfbXopdiaTfL0r7xcAALh5sMSoimbMmKHffvtNbdq00fz585WVlaVdu3Zpzpw5+umnn2Rvf/5T2E6dOikkJETJycnaunWrNm3apN69eysmJsZmOUz37t1VUFCgZ555RrGxsWrSpIlxbPDgwfrll1+UlJSkjIwMZWdna9WqVerbt2+V3yhXpEWLFlq8eLEsFou2b9+uxx57zJgZqKqkpCR5eXmpW7duSk9P1759+7Ro0SJt3LhRkvTyyy/rs88+04QJE7Rjxw5lZWVp3rx5GjNmTLnt7d+/X6NGjdLGjRt18OBBrV69Wnv27DGeQ/Dz89P+/ftlsVj0888/26zRv1hUVJTq16+v0aNHKzs7W3PnzjW+9eiCcePG6fPPP9e4ceOUlZWlzMxMm9kaPz8/rV+/Xv/5z3+Mb47q0KGDjh8/rrfeekvZ2dl677339MUXX1Q6VsnJyWrUqJEefvhhbdiwQfv379fatWs1dOhQHT58uNL61eHi7KjmPm7VqtPcx41fVgYAADYICFV0++23a9u2berUqZNGjRqlsLAwtWnTRu+++65SUlKMB45NJpP++c9/ysPDQ/fee686deqk5s2ba/78+Tbtubi4KCEhQdu3b1dycrLNsSZNmig9PV0lJSW6//77FRISomHDhsnd3V12dlf2TzZlyhR5eHioffv2SkhIUFxcnCIiIqrVhqOjo1avXq1bbrlFDzzwgEJCQjRx4kQjJMXFxWn58uVavXq12rZtq3bt2mnq1Klq1qxZue3Vr19fP/30kxITExUQEKCnnnpKgwcP1sCBAyVJiYmJio+PV2xsrDw9PfX5559X2LcGDRpozpw5WrFihUJCQvT5559r/PjxNmU6dOighQsXatmyZbrjjjvUsWNHbdq0yTj+yiuv6MCBA7r99tuNZUBBQUGaMWOG3nvvPYWFhWnTpk1KSUmpdKzq16+v9evXy9fXV927d1dQUJD69eunM2fOVGlGobruDPGWvZ2p8oKS7O1NujPEu/KCAADgpmKyXrywGsANIz8/X25ubjp9+nSVA8XenJP697pL/1iavZ1JXWOay9/X42p1FQBuCpfzdxmoaZhBAGoZf18P9ewSKH9fd9ld9ANxdiaT/H3d/3uccAAAAMriIWWgFvJq5KyHYv1VUHRWObn5OnuuRI4O9vL1duWZAwAAcEkEBKAWc3F25EfQAABAtbDECAAAAICBgAAAAADAQEAAAAAAYCAgAAAAADAQEAAAAAAYCAgAAAAADAQEAAAAAAYCAgAAAAADAQEAAACAgYAAAAAAwEBAAAAAAGAgIAAAAAAwEBAAAAAAGAgIAAAAAAwEBAAAAAAGAgIAAAAAAwEBAAAAgIGAAAAAAMBAQAAAAABgICAAAAAAMBAQAAAAABgICAAAAAAMBAQAAAAABgICAAAAAAMBAQAAAICBgAAAAADAQEAAAAAAYCAgAAAAADAQEAAAAAAYCAgAAAAADAQEAAAAAAYCAgAAAAADAQEAAACAgYAAAAAAwEBAAAAAAGAgIAAAAAAwEBAAAAAAGAgIAAAAAAwEBAAAAAAGAgIAAAAAQ53r3QEAAIBroaDorHJy81V8rkRODvby9XaVi7Pj9e4WcMNhBqGWGj9+vO64445LlunQoYOGDRt21c7Zp08fdevW7aq190eaPXu23N3da1zbAIDqy/u5SMu+3quPF2VqVfoBrd10SKvSD+jjRZla9vVe5f1cdL27CNxQCAg3uD59+shkMpXZ4uPjjTImk0lLly6tdtuLFy9WamrqVezt5Vu7dq1MJpNOnTp1vbsCAKhF9hw8qflf/KS9OadUarXaHCu1WrU359R/j5+8Tj0EbjwsMaoB4uPjNWvWLJt9Tk5OV9xugwYNrriNm9nZs2fl6MjUNADcqPJ+LtKK9ftUUmq9ZLmSUqv+vW6fenYJlFcj52vUO+DGxQxCDeDk5CQvLy+bzcPDQ5Lk5+cnSXrkkUdkMpmM1xf87W9/k5+fn9zc3NSrVy8VFBQYxy5eYlRcXKwXX3xRPj4+cnJykr+/vz7++GNJUklJifr166fbbrtN9erVU8uWLTVt2rRqXcfBgweVkJAgDw8POTs7Kzg4WCtWrNCBAwcUGxsrSfLw8JDJZFKfPn0kSStXrtTdd98td3d3NWzYUA8++KCys7ONNg8cOCCTyaTFixcrNjZW9evXV1hYmDZu3Ghz7tmzZ8vX11f169fXI488ohMnTtgcz87O1sMPP6zGjRvLbDarbdu2+vLLL23K+Pn5KTU1Vb1795arq6ueeuqpKrW9fft2xcbGysXFRa6uroqMjNTmzZurNXYAgOrblJlbaTi4oKTUqk2ZuX9wj4CagYBQw2VkZEiSZs2apdzcXOO1dP5N79KlS7V8+XItX75c69at08SJEytsq3fv3vr888/1zjvvKCsrSx988IHMZrMkqbS0VE2bNtXChQu1c+dOvfzyyxo9erQWLFhQ5b4OHjxYxcXFWr9+vTIzM/Xmm2/KbDbLx8dHixYtkiTt2rVLubm5RvgoKirS8OHDtXnzZq1Zs0Z2dnZ65JFHVFpaatP2Sy+9pJSUFFksFgUEBCgpKUm//fabJOn7779Xv379NGTIEFksFsXGxurVV1+1qV9YWKgHHnhAa9as0bZt2xQfH6+EhATl5OTYlJs0aZLCwsK0bds2jR07tkptJycnq2nTpsrIyNCWLVs0cuRIOTg4VHncAADVV1B0VtmHTlWrzr5Dp1VQdPaP6RBQg7DEqAZYvny58Ub9gtGjR2v06NHy9PSUJLm7u8vLy8umTGlpqWbPni0XFxdJ0uOPP641a9botddeK3OO3bt3a8GCBUpLS1OnTp0kSc2bNzeOOzg4aMKECcbr2267TRs3btSCBQvUo0ePKl1HTk6OEhMTFRISUqb9C8udbrnlFpsHfBMTE23a+OSTT+Tp6amdO3eqdevWxv6UlBR17dpVkjRhwgQFBwdr7969CgwM1LRp0xQfH68XXnhBkhQQEKBvv/1WK1euNOqHhYUpLCzMeJ2amqolS5Zo2bJlGjJkiLG/Y8eOGjFihPF67Nixlbadk5Ojv/zlLwoMDJQktWjRosIxKi4uVnFxsfE6Pz+/wrIAgIrl5ObLWrXJA0Op1aqc3HwF+zf6YzoF1BDMINQAsbGxslgsNtvTTz9daT0/Pz8jHEiSt7e3jh07Vm5Zi8Uie3t7xcTEVNjee++9p8jISHl6espsNuvDDz8s8wn7pQwdOlSvvvqq7rrrLo0bN04//PBDpXX27NmjpKQkNW/eXK6ursYSqovPGxoaavy3t7e3JBnXmpWVpaioKJvy0dHRNq8LCwuVkpKioKAgubu7y2w2Kysrq8x52rRpY/O6Km0PHz5c/fv3V6dOnTRx4kSbJVIXe+ONN+Tm5mZsPj4+FZYFAFSs+FzJZdU7e5n1gNqEgFADODs7y9/f32arygPGFy9jMZlMZZbmXFCvXr1LtjVv3jylpKSoX79+Wr16tSwWi/r27auzZ6s+Fdu/f3/t27dPjz/+uDIzM9WmTRu9++67l6yTkJCgX375RR999JG+//57ff/995JU5ry/v1aTySRJFV5reVJSUrRkyRK9/vrr2rBhgywWi0JCQsqcx9m5+g+vjR8/Xjt27FDXrl311VdfqVWrVlqyZEm5ZUeNGqXTp08b26FDh6p9PgCA5ORgf1n1HC+zHlCbEBBqAQcHB5WUXNknHiEhISotLdW6devKPZ6enq727dtr0KBBCg8Pl7+//yU/Ca+Ij4+Pnn76aS1evFgjRozQRx99JEnGtwH9/jpOnDihXbt2acyYMbrvvvsUFBSkkyer/zV0QUFBRrC44LvvvrN5nZ6erj59+uiRRx5RSEiIvLy8dODAgavStnR+6dHzzz+v1atXq3v37mW+leoCJycnubq62mwAgOrz9XaV3X8/MKoqO5NJvt783QUICDVAcXGx8vLybLaff/7ZOO7n56c1a9YoLy/vst5AX2jjiSee0JNPPqmlS5dq//79Wrt2rfEQcosWLbR582atWrVKu3fv1tixY20eiK6KYcOGadWqVdq/f7+2bt2qr7/+WkFBQZKkZs2ayWQyafny5Tp+/LgKCwvl4eGhhg0b6sMPP9TevXv11Vdfafjw4dW+tqFDh2rlypWaNGmS9uzZo+nTp9s8I3Dh+hYvXiyLxaLt27frscceq9IMRGVt//rrrxoyZIjWrl2rgwcPKj09XRkZGcZ1AwD+GC7Ojmru41atOs193PhlZUAEhBph5cqV8vb2ttnuvvtu4/jkyZOVlpYmHx8fhYeHX/Z53n//fT366KMaNGiQAgMDNWDAABUVnf91yYEDB6p79+7q2bOnoqKidOLECQ0aNKha7ZeUlGjw4MEKCgpSfHy8AgICNGPGDEnSrbfeqgkTJmjkyJFq3LixhgwZIjs7O82bN09btmxR69at9fzzz+vtt9+u9nW1a9dOH330kaZNm6awsDCtXr1aY8aMsSkzZcoUeXh4qH379kpISFBcXJwiIiKuuG17e3udOHFCvXv3VkBAgHr06KEuXbrYPPANAPhj3BniLXu7qs0i2NubdGeI9x/cI6BmMFmt1X3GH8C1kp+fLzc3N50+fZrlRgBwGfbmnNS/1136x9Ls7UzqGtNc/r4elbbH32XcDJhBAAAAtZa/r4d6dgmUv697mWcS7Ewm+fu6//d45eEAuFnwOwgAAKBW82rkrIdi/VVQdFY5ufk6e65Ejg728vV25ZkDoBwEBAAAcFNwcXbkR9CAKmCJEQAAAAADAQEAAACAgYAAAAAAwEBAAAAAAGAgIAAAAAAwEBAAAAAAGAgIAAAAAAwEBAAAAAAGAgIAAAAAAwEBAAAAgIGAAAAAAMBAQAAAAABgICAAAAAAMBAQAAAAABgICAAAAAAMBAQAAAAABgICAAAAAAMBAQAAAIChzvXuAICKWa1WSVJ+fv517gkAQPrf3+MLf5+B2oiAANzACgoKJEk+Pj7XuScAgN8rKCiQm5vb9e4G8IcwWYnAwA2rtLRUR44ckYuLi0wm02W1kZ+fLx8fHx06dEiurq5XuYc3B8bwyjGGV44xvDqudBytVqsKCgrUpEkT2dmxUhu1EzMIwA3Mzs5OTZs2vSptubq68qbiCjGGV44xvHKM4dVxJePIzAFqO6IvAAAAAAMBAQAAAICBgADUck5OTho3bpycnJyud1dqLMbwyjGGV44xvDoYR6ByPKQMAAAAwMAMAgAAAAADAQEAAACAgYAAAAAAwEBAAGqw999/X6Ghocb3eUdHR+uLL764ZJ2FCxcqMDBQdevWVUhIiFasWHGNentjqu4Yzp49WyaTyWarW7fuNezxjW/ixIkymUwaNmzYJctxL1asKmPIvVjW+PHjy4xJYGDgJetwHwJlERCAGqxp06aaOHGitmzZos2bN6tjx456+OGHtWPHjnLLf/vtt0pKSlK/fv20bds2devWTd26ddOPP/54jXt+46juGErnf2ApNzfX2A4ePHgNe3xjy8jI0AcffKDQ0NBLluNerFhVx1DiXixPcHCwzZh88803FZblPgQqYAVQq3h4eFhnzpxZ7rEePXpYu3btarMvKirKOnDgwGvRtRrjUmM4a9Ysq5ub27XtUA1RUFBgbdGihTUtLc0aExNjfe655yosy71YvuqMIfdiWePGjbOGhYVVuTz3IVA+ZhCAWqKkpETz5s1TUVGRoqOjyy2zceNGderUyWZfXFycNm7ceC26eMOryhhKUmFhoZo1ayYfH59KZxtuJoMHD1bXrl3L3GPl4V4sX3XGUOJeLM+ePXvUpEkTNW/eXMnJycrJyamwLPchUL4617sDAK5MZmamoqOjdebMGZnNZi1ZskStWrUqt2xeXp4aN25ss69x48bKy8u7Fl29YVVnDFu2bKlPPvlEoaGhOn36tCZNmqT27dtrx44datq06TXu+Y1j3rx52rp1qzIyMqpUnnuxrOqOIfdiWVFRUZo9e7Zatmyp3NxcTZgwQffcc49+/PFHubi4lCnPfQiUj4AA1HAtW7aUxWLR6dOn9Y9//ENPPPGE1q1bV+EbXJRVnTGMjo62mV1o3769goKC9MEHHyg1NfVadvuGcejQIT333HNKS0u76R+SvVyXM4bci2V16dLF+O/Q0FBFRUWpWbNmWrBggfr163cdewbULAQEoIZzdHSUv7+/JCkyMlIZGRmaNm2aPvjggzJlvby8dPToUZt9R48elZeX1zXp642qOmN4MQcHB4WHh2vv3r1/dDdvWFu2bNGxY8cUERFh7CspKdH69es1ffp0FRcXy97e3qYO96KtyxnDi3EvluXu7q6AgIAKx4T7ECgfzyAAtUxpaamKi4vLPRYdHa01a9bY7EtLS7vkevub0aXG8GIlJSXKzMyUt7f3H9yrG9d9992nzMxMWSwWY2vTpo2Sk5NlsVjKfWPLvWjrcsbwYtyLZRUWFio7O7vCMeE+BMrHDAJQg40aNUpdunSRr6+vCgoKNHfuXK1du1arVq2SJPXu3Vu33nqr3njjDUnSc889p5iYGE2ePFldu3bVvHnztHnzZn344YfX8zKuq+qO4SuvvKJ27drJ399fp06d0ttvv62DBw+qf//+1/MyrisXFxe1bt3aZp+zs7MaNmxo7OdevLTLGUPuxbJSUlKUkJCgZs2a6ciRIxo3bpzs7e2VlJQkifsQqCoCAlCDHTt2TL1791Zubq7c3NwUGhqqVatWqXPnzpKknJwc2dn9b6Kwffv2mjt3rsaMGaPRo0erRYsWWrp0aZk3JjeT6o7hyZMnNWDAAOXl5cnDw0ORkZH69ttveeajEtyLV457sXKHDx9WUlKSTpw4IU9PT91999367rvv5OnpKYn7EKgqk9VqtV7vTgAAAAC4MfAMAgAAAAADAQEAAACAgYAAAAAAwEBAAAAAAGAgIAAAAAAwEBAAAAAAGAgIAAAAAAwEBAAAAAAGAgIA4Lq79957NXfu3Gt2vpEjR+rZZ5+9ZucDgJqEgAAAtczx48f1zDPPyNfXV05OTvLy8lJcXJzS09Ovd9fKtWzZMh09elS9evUy9p05c0aDBw9Ww4YNZTablZiYqKNHj1apvQMHDshkMpXZvvvuO6NMSkqKPv30U+3bt++qXw8A1HQEBACoZRITE7Vt2zZ9+umn2r17t5YtW6YOHTroxIkTf9g5z549e9l133nnHfXt21d2dv/7X9Lzzz+vf/3rX1q4cKHWrVunI0eOqHv37tVq98svv1Rubq6xRUZGGscaNWqkuLg4vf/++5fdbwCorQgIAFCLnDp1Shs2bNCbb76p2NhYNWvWTHfeeadGjRqlhx56yKbcwIED1bhxY9WtW1etW7fW8uXLjeOLFi1ScHCwnJyc5Ofnp8mTJ9ucx8/PT6mpqerdu7dcXV311FNPSZK++eYb3XPPPapXr558fHw0dOhQFRUVVdjf48eP66uvvlJCQoKx7/Tp0/r44481ZcoUdezYUZGRkZo1a5a+/fZbm1mAyjRs2FBeXl7G5uDgYHM8ISFB8+bNq3J7AHCzICAAQC1iNptlNpu1dOlSFRcXl1umtLRUXbp0UXp6uubMmaOdO3dq4sSJsre3lyRt2bJFPXr0UK9evZSZmanx48dr7Nixmj17tk07kyZNUlhYmLZt26axY8cqOztb8fHxSkxM1A8//KD58+frm2++0ZAhQyrs7zfffKP69esrKCjI2LdlyxadO3dOnTp1MvYFBgbK19dXGzdurPJYPPTQQ7rlllt09913a9myZWWO33nnnTp8+LAOHDhQ5TYB4GZQ53p3AABw9dSpU0ezZ8/WgAED9Ne//lURERGKiYlRr169FBoaKun80ptNmzYpKytLAQEBkqTmzZsbbUyZMkX33Xefxo4dK0kKCAjQzp079fbbb6tPnz5GuY4dO2rEiBHG6/79+ys5OVnDhg2TJLVo0ULvvPOOYmJi9P7776tu3bpl+nvw4EE1btzYZnlRXl6eHB0d5e7ublO2cePGysvLq3QMzGazJk+erLvuukt2dnZatGiRunXrpqVLl9rMojRp0sTog5+fX6XtAsDNghkEAKhlEhMTdeTIES1btkzx8fFau3atIiIijBkAi8Wipk2bGuHgYllZWbrrrrts9t11113as2ePSkpKjH1t2rSxKbN9+3bNnj3bmMUwm82Ki4tTaWmp9u/fX+65fv3113KDQ2WCg4NtzmM2m9WlSxdJ558vGD58uKKiotS2bVtNnDhRf/7zn/X222/btFGvXj1J0v/93/9V+/wAUJsxgwAAtVDdunXVuXNnde7cWWPHjlX//v01btw49enTx3hjfKWcnZ1tXhcWFmrgwIEaOnRombK+vr7lttGoUSOdPHnSZp+Xl5fOnj2rU6dO2cwiHD16VF5eXpKkFStW6Ny5czb1LnVdUVFRSktLs9n3yy+/SJI8PT0rrAcANyMCAgDcBFq1aqWlS5dKkkJDQ3X48GHt3r273FmEoKCgMl+Jmp6eroCAAOM5hfJERERo586d8vf3r3K/wsPDlZeXp5MnT8rDw0OSFBkZKQcHB61Zs0aJiYmSpF27diknJ0fR0dGSpGbNmlX5HNL5WRNvb2+bfT/++KMcHBwUHBxcrbYAoLYjIABALXLixAn96U9/0pNPPqnQ0FC5uLho8+bNeuutt/Twww9LkmJiYnTvvfcqMTFRU6ZMkb+/v3766SeZTCbFx8drxIgRatu2rVJTU9WzZ09t3LhR06dP14wZMy557hdffFHt2rXTkCFD1L9/fzk7O2vnzp1KS0vT9OnTy60THh6uRo0aKT09XQ8++KAkyc3NTf369dPw4cPVoEEDubq66tlnn1V0dLTatWtX6Rh8+umncnR0VHh4uCRp8eLF+uSTTzRz5kybchs2bDC+cQkA8D8EBACoRcxms6KiojR16lRlZ2fr3Llz8vHx0YABAzR69Gij3KJFi5SSkqKkpCQVFRXJ399fEydOlHR+JmDBggV6+eWXlZqaKm9vb73yyis2DyiXJzQ0VOvWrdNLL72ke+65R1arVbfffrt69uxZYR17e3v17dtXf//7342AIElTp06VnZ2dEhMTVVxcrLi4uEoDyu+lpqbq4MGDqlOnjgIDAzV//nw9+uijNmXmzZun8ePHV7lNALhZmKxWq/V6dwIAcPPKy8tTcHCwtm7dWu2lQ5friy++0IgRI/TDDz+oTh0+KwOA3+NbjAAA15WXl5c+/vhj5eTkXLNzFhUVadasWYQDACgHMwgAAAAADMwgAAAAADAQEAAAAAAYCAgAAAAADAQEAAAAAAYCAgAAAAADAQEAAACAgYAAAAAAwEBAAAAAAGAgIAAAAAAwEBAAAAAAGP4fCWtBthpu1l4AAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Step 5: Exploration\n",
        "\n",
        "Now that you have successfully generated, interpreted, and visualized ESG scores using Gemini, it is time to experiment. This step encourages iterative prompt testing, model comparison, and creative extensions to explore the full potential and limitations of using LLMs for semantic ESG analysis.\n",
        "\n",
        "This lab encourages you to try two different Gemini-based models for comparison:\n",
        "\n",
        "1. **Gemini 2.0 Flash**\n",
        "  - Fast and cost-efficient\n",
        "  - Good for quick testing or bulk document processing\n",
        "\n",
        "2. **Gemini 2.5 (Preview)**\n",
        "  - Most advanced and semantically nuanced\n",
        "  - Good at maintaining structure, depth, and subtle distinctions\n",
        "  - Recommended for detailed ESG analysis or comparison tasks\n",
        "\n",
        "> Note: Both models are available under Google’s Free Tier, but be aware that request rate limits apply.\n",
        "For example, Gemini 2.0 Flash typically allows up to 10 requests per minute. If you make too many rapid calls, you may encounter errors or delays.\n",
        "Please plan your testing intervals accordingly and wait a few seconds between runs if needed.\n",
        "\n",
        "By running the same prompt on each model, you can observe differences in:\n",
        "\n",
        "- Scoring accuracy: Do scores feel grounded in the actual PDF content?\n",
        "- Justification depth:\tAre explanations vague or specific? Do they cite evidence?\n",
        "- Output structure:\tAre tables formatted cleanly? Are any fields missing?\n",
        "- Responsiveness:\tDoes the model ignore parts of the prompt or skip items?\n",
        "- Hallucination risk:\tAre there statements not supported by the text?\n"
      ],
      "metadata": {
        "id": "5Evw2aal0LJ1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Try different models\n",
        "\n",
        "model = genai.GenerativeModel(\"gemini-2.0-flash\")\n",
        "# model = genai.GenerativeModel(\"models/gemini-1.5-pro-latest\")\n",
        "\n",
        "response = model.generate_content(\n",
        "    [\n",
        "        {\"text\": prompt},\n",
        "        {\"mime_type\": \"application/pdf\", \"data\": pdf_content},\n",
        "    ]\n",
        ")\n",
        "\n",
        "print(response.text)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 315
        },
        "id": "lL7w7D7k2GBU",
        "outputId": "944acfb6-bcc7-4c57-8ca7-cd7591f1e97d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Okay, here's the requested ESG analysis of the provided NVIDIA Sustainability Report for Fiscal Year 2024.\n",
            "\n",
            "**Table of ESG Theme Assessment**\n",
            "\n",
            "| Category      | Item                                            | Score | Justification                                                                                                                                                  |\n",
            "| :------------ | :---------------------------------------------- | :---- | :------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n",
            "| Environmental | Carbon neutrality or climate pledges              | 3     | NVIDIA has a target to achieve 100% renewable electricity use, but it doesn't mention carbon neutrality or a firm climate pledge                               |\n",
            "| Environmental | Use of measurable, time-bound environmental goals | 5     | The report explicitly outlines time-bound goals (e.g., 100% renewable electricity by FY25, engaging suppliers by FY26) and quantifies progress using metrics. |\n",
            "| Environmental | Emphasis on technology and innovation for sustainability | 5     | The report emphasizes how NVIDIA's accelerated computing and AI are helping solve climate challenges and increase energy efficiency.                   |\n",
            "| Social        | Diversity, equity, and inclusion (DEI) focus     | 5     | There is a strong focus on DEI, including recruitment, retention, pay equity, and supporting community resource groups.                                   |\n",
            "| Social        | Community engagement and small business support | 3     | There is some discussion of community resource groups and the Inception program for climate startups, but it could be more developed.               |\n",
            "| Social        | Stakeholder participation or employee empowerment | 3     | Employee feedback is mentioned as a source for improvements. There is mention of mentorship programs and \"Speak Up\" hotline, but it could be more emphatic. |\n",
            "| Governance    | Risk and compliance transparency               | 3     | The report discusses risk assessments, cybersecurity, and compliance with the RBA code of conduct, but deeper transparency would improve credibility.                                                      |\n",
            "| Governance    | Corporate governance structure and oversight  | 3     | The Board's and a committee's oversight of sustainability is mentioned, however details about these groups and their activities would improve this score.         |\n",
            "| Governance    | Ethical standards and trust-building         | 5     | There is significant emphasis on ethics, a code of conduct, trustworthy AI, and mechanisms for raising concerns.                                            |\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Step 6: Comparison with Traditional Methods\n",
        "\n",
        "To better understand the strengths and limitations of LLM-based ESG analysis, it is useful to compare Gemini’s semantic outputs with traditional text analysis techniques.\n",
        "\n",
        "This section focuses on two baseline methods:\n",
        "\n",
        "- Keyword frequency analysis: What terms show up most often?\n",
        "- Sentiment analysis: What is the tone or emotional framing of the ESG language?\n",
        "\n",
        "> These methods are more quantitative and transparent than LLMs, but they may miss context, nuance, and indirect phrasing."
      ],
      "metadata": {
        "id": "kdOH4drA2t6O"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Keyword frequency analysis\n",
        "\n",
        "from collections import Counter\n",
        "import re\n",
        "\n",
        "text = pdf_content.decode(\"latin-1\", errors=\"ignore\")  # fallback if UTF-8 fails\n",
        "\n",
        "tokens = re.findall(r'\\b[a-z]{3,}\\b', text.lower())\n",
        "\n",
        "esg_keywords = [\n",
        "    \"sustainability\", \"climate\", \"carbon\", \"net zero\", \"renewable\",\n",
        "    \"diversity\", \"equity\", \"inclusion\", \"community\", \"ethics\",\n",
        "    \"governance\", \"compliance\", \"risk\", \"board\", \"stakeholder\"\n",
        "]\n",
        "\n",
        "keyword_counts = Counter([word for word in tokens if word in esg_keywords])\n",
        "\n",
        "for word, count in keyword_counts.most_common():\n",
        "    print(f\"{word}: {count}\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bL37DJH33F9b",
        "outputId": "3e7925ad-0dd8-4c67-c594-d16c97d373bd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "sustainability: 83\n",
            "diversity: 82\n",
            "inclusion: 80\n",
            "climate: 78\n",
            "governance: 2\n",
            "renewable: 1\n",
            "risk: 1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install textblob\n",
        "from textblob import TextBlob\n",
        "\n",
        "# Convert full text to blob and assess sentiment\n",
        "blob = TextBlob(text)\n",
        "print(\"Overall polarity score:\", blob.sentiment.polarity)  # -1 (negative) to 1 (positive)\n",
        "print(\"Subjectivity score:\", blob.sentiment.subjectivity)  # 0 (objective) to 1 (subjective)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "C6E9w_Qt3Qcd",
        "outputId": "bde16fb1-e940-470a-b5f4-a5579d8826c6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: textblob in /usr/local/lib/python3.11/dist-packages (0.19.0)\n",
            "Requirement already satisfied: nltk>=3.9 in /usr/local/lib/python3.11/dist-packages (from textblob) (3.9.1)\n",
            "Requirement already satisfied: click in /usr/local/lib/python3.11/dist-packages (from nltk>=3.9->textblob) (8.2.1)\n",
            "Requirement already satisfied: joblib in /usr/local/lib/python3.11/dist-packages (from nltk>=3.9->textblob) (1.5.1)\n",
            "Requirement already satisfied: regex>=2021.8.3 in /usr/local/lib/python3.11/dist-packages (from nltk>=3.9->textblob) (2024.11.6)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.11/dist-packages (from nltk>=3.9->textblob) (4.67.1)\n",
            "Overall polarity score: 0.16517421114378647\n",
            "Subjectivity score: 0.8510951691986178\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Step 7: Critical Reflection\n",
        "\n",
        "In this lab, you explored how large language models like Google Gemini can be applied to ESG analysis by interpreting sustainability reports through structured prompting. You generated semantic scores, visualized model outputs, and compared them against traditional methods like keyword frequency and sentiment analysis. Along the way, you critically evaluated the strengths and shortcomings of LLMs, including issues of transparency, bias, and reliability. Ultimately, this lab highlights both the promise and complexity of using AI to interpret corporate sustainability narratives across cultural and regulatory contexts.\n",
        "\n",
        "This final step asks you to critically assess the value, challenges, and implications of using LLMs, such as Gemini, for ESG discourse analysis.\n",
        "\n",
        "While LLMs can offer rapid, scalable insights into sustainability reports, they are not without limitations. Comparing these AI-based interpretations with traditional NLP techniques and human judgment helps surface key tensions in using generative AI for corporate accountability.\n",
        "\n",
        "### Key Areas for Reflection\n",
        "\n",
        "1. Interpretability and Trust\n",
        "  - Did Gemini’s justifications seem grounded in actual report content?\n",
        "  - Could you trace why it gave a specific score, or did it feel like a black box?\n",
        "  - Would you trust these scores for investing, policymaking, or ranking companies?\n",
        "\n",
        "2. Cultural and Linguistic Bias\n",
        "  - Did the model interpret non-Western ESG narratives differently?\n",
        "  - How might language tone, translation, or regulatory norms affect how LLMs score a report?\n",
        "\n",
        "3. Model Limitations\n",
        "  - Gemini sometimes skips categories, hallucinates content, or gives vague explanations.\n",
        "  - Output formatting is inconsistent, especially across longer reports or with complex prompts.\n",
        "  - Unlike traditional methods, Gemini can't show its work, just its conclusions.\n",
        "\n",
        "4. Traditional Methods: Too Shallow?\n",
        "  - Keyword frequency tells us what’s repeated, but not what’s prioritized.\n",
        "  - Sentiment analysis lacks nuance, as a positive tone does not real accountability.\n",
        "  - Yet, these methods are fully auditable and reproducible.\n",
        "\n",
        "5. Prompt Engineering Challenges\n",
        "  - Small changes in phrasing dramatically alter the model’s output.\n",
        "  - How much responsibility does the user have for the quality of the model’s judgment?\n",
        "\n",
        "### Final Questions\n",
        "\n",
        "- How would you combine AI-driven and human-centered methods for ESG evaluation?\n",
        "- Is it ethical to use LLMs to rate companies on sustainability without disclosing the opacity of the method?\n",
        "- Should organizations be required to use explainable, transparent tools when automating ESG assessments?\n",
        "- What does this lab reveal about how AI understands not just language, but values?\n"
      ],
      "metadata": {
        "id": "26TVQo_K3n2y"
      }
    }
  ]
}